Browsing by Subject "Verhaltensökonomie"

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Behavioral economic impact on animal health surveillance system in Thailand
(2021) Kewprasopsak, Tossapond; Reiner, Doluschitz
Zoonotic diseases are a continuously significant threat to global human and livestock health (causing millions of deaths yearly). Zoonotic diseases are not only a human health threat, but also a threat to animal health and welfare. Moreover, they have a high impact on national economies and food security due to productivity and production reduction. Expanding worldwide travel and global trade increases the importance of the threat of zoonotic diseases. The increase in global meat consumption contrasts with the escalating instability of the global meat market, which is affected by the increase of livestock densities, changes in production intensity, and slaughtering systems, causing animal disease outbreaks to spread widely. This study focuses on the animal disease surveillance system in Thailand as an important world meat exporter. In 2014, the Participatory One Health Disease Detection project, or PODD was set up by the veterinary inspection authorities to test animal epidemic control systems using smartphone applications in the Chiang Mai province in northern Thailand The main objectives of this study are (i) to evaluate the economic impact of the PODD system on farmers by impact assessment (n = 177) (ii) to demonstrate the impact of monetary and non-monetary incentives on the PODD reporters by the experimental approach (n = 17), (iii) and to present the effect of the socioeconomic factors and behavioral bias on farmers animal disease reporting behavior with the logit model (n = 467). Focusing on the first objective, the results of this study concluded that there is an impact on the farmers. The technology alone cannot improve animal health security in the short-term. In the second objective, the results concluded that, in the case of the PODD reporters, the decision of using monetary incentives to motivate most of the PODD reporters has a negative impact in the long-term. Losing reporter motivation and effort reflected to the low efficiency of the digital surveillance system of PODD and no impact on farmers. Concerning In the last objective, the results concluded that the optimistic bias of farmers has a very high impact on their decision making about reporting animal diseases on their farm. Just one infected farm in the case of dairy milk farmers can spread the foot-and-mouth disease to other farms. The new digital animal health surveillance system alone is not enough to reduce the impact of animal diseases of farmers. Suitable motivation for the reports and awareness of farmers optimistic bias in animal disease reporting cannot be neglected in digital animal disease surveillance system improvement. Overall, it can be concluded that the digital animal disease surveillance system is a powerful instrument for reducing the impact of animal diseases and increasing food safety and security. However, application of this advanced technology still needs time to demonstrate the impact and to be broadly adopted by users. In terms of motivation, the monetary incentive can increase the effort of report in the short run but it comes at a high cost and has a negative impact in the long-term. While the social incentive costs less and is more effective in the long-term. Where farmers’ animal disease reporting behavior is concerned, the optimistic bias is the highest influential factor on the farmers reporting decisions, in an inverse correlation.
Behavioral economic impact on animal health surveillance system in Thailand (correct version of the dissertation)
(2021) Kewprasopsak, Tossapond
Zoonotic diseases are a continuously significant threat to global human and livestock health (causing millions of deaths yearly). Zoonotic diseases are not only a human health threat, but also a threat to animal health and welfare. Moreover, they have a high impact on national economies and food security due to productivity and production reduction. Expanding worldwide travel and global trade increases the importance of the threat of zoonotic diseases. The increase in global meat consumption contrasts with the escalating instability of the global meat market, which is affected by the increase of livestock densities, changes in production intensity, and slaughtering systems, causing animal disease outbreaks to spread widely. This study focuses on the animal disease surveillance system in Thailand as an important world meat exporter. In 2014, the Participatory One Health Disease Detection project, or PODD was set up by the veterinary inspection authorities to test animal epidemic control systems using smartphone applications in the Chiang Mai province in northern Thailand The main objectives of this study are (i) to evaluate the economic impact of the PODD system on farmers by impact assessment (n = 177) (ii) to demonstrate the impact of monetary and non-monetary incentives on the PODD reporters by the experimental approach (n = 17), (iii) and to present the effect of the socioeconomic factors and behavioral bias on farmers animal disease reporting behavior with the logit model (n = 467). Focusing on the first objective, the results of this study concluded that there is an impact on the farmers. The technology alone cannot improve animal health security in the short-term. In the second objective, the results concluded that, in the case of the PODD reporters, the decision of using monetary incentives to motivate most of the PODD reporters has a negative impact in the long-term. Losing reporter motivation and effort reflected to the low efficiency of the digital surveillance system of PODD and no impact on farmers. Concerning In the last objective, the results concluded that the optimistic bias of farmers has a very high impact on their decision making about reporting animal diseases on their farm. Just one infected farm in the case of dairy milk farmers can spread the foot-and-mouth disease to other farms. The new digital animal health surveillance system alone is not enough to reduce the impact of animal diseases of farmers. Suitable motivation for the reports and awareness of farmers optimistic bias in animal disease reporting cannot be neglected in digital animal disease surveillance system improvement. Overall, it can be concluded that the digital animal disease surveillance system is a powerful instrument for reducing the impact of animal diseases and increasing food safety and security. However, application of this advanced technology still needs time to demonstrate the impact and to be broadly adopted by users. In terms of motivation, the monetary incentive can increase the effort of report in the short run but it comes at a high cost and has a negative impact in the long-term. While the social incentive costs less and is more effective in the long-term. Where farmers animal disease reporting behavior is concerned, the optimistic bias is the highest influential factor on the farmers’ reporting decisions, in an inverse correlation.
Investor sentiment in blogs : design of a classifier and validation by a portfolio simulation
(2016) Klein, Achim; Kirn, Stefan
How can investment recommendations available on the web significantly improve stock selection? This dissertation shows how online investment recommendations can automatically be analyzed, aggregated, and used to achieve a return above the market’s. To this respect, it is crucial to understand how investment recommendations affect returns. Therefore, the dissertation examines the effects of direct and indirect investment recommendations from blogs in the form of investor sentiments (i.e., opinions) on the expected development of stock prices. Blogs have made it possible for everyone to publish articles on the web. The studied blog platforms Seekingalpha and Blogspot host a wealth of semi-professional stock analyses, investor opinions, company rumors, and stock recommendations. The dissertation’s study uses about 77,000 articles from Seekingalpha and about 198,000 articles from Blogspot over a five-year period (2007-2011). A novel text classification method is developed for the automatic classification of blog articles in a positive vs. negative sentiment. To achieve a high classification accuracy, experiments were carried out to configure this method. The text classification method uses machine learning techniques, which learn from manually classified articles from a novel corpus. Using behavioral finance theory, hypotheses are developed about the effects of investor sentiments on a portfolios returns. To test these hypotheses, a monthly selection of stocks of the Dow Jones Industrial Average into a portfolio was simulated (i.e., backtested). The selection is made by means of the ranking of the monthly aggregated overall sentiment of all articles regarding a specific stock. The results show that a return above the market’s can be achieved with aggregated investor sentiments from the Seekingalpha platform. In most cases, the achieved return exceeds the return of a momentum portfolio based solely on past returns. For the platform Blogspot, results are weaker. Overall, it seems advisable for investors to select a small number of stocks based on the most positive and most negative monthly investor sentiments from professional blogs.
Non-trading behaviour in choice experiments
(2016) Neidhardt, Jan; Ahlheim, Michael
This paper addresses a methodological problem of choice experiments, namely the problem that respondents sometimes avoid the intellectual effort of thoroughly considering the trade-offs between different alternatives that are the essence of every choice experiment, and tick instead the next best alternative without the necessary deliberation. This kind of behaviour which is called "nontrading" in the respective literature calls into question the validity of choice experiments. In this paper, which is based on an online choice experiment concerned with consumer’s tastes for table grapes with 1,000 participants, we suggest possibilities to identify potential non-traders not only by their answering behaviour but also by some general characteristics we found to be typical of this kind of respondent.
The rise of behavioural economics : a quantitative assessment
(2015) Geiger, Niels
This paper is devoted to the question of operationalising the development of behavioural economics, focussing on trends in the academic literature. The main research goal is to provide a quantitative assessment in order to answer the question of whether or not behavioural economics has gained in relative importance in the past few years. After an introduction and a short summary of the history of behavioural economics, several studies are laid out and evaluated. The results generally confirm the story as it is usually told in the literature, and add some notable additional insights.
Wellen wirtschaftlichen Wandels – theoretische, historische und statistische Betrachtung
(2015) Geiger, Niels; Hagemann, Harald
This dissertation provides an elaborate discussion of business cycle theory. In particular, the question of peculiarities of individual agents’ behaviour within an economy is analysed: Can macroeconomic fluctuations in various variables, such as production, unemployment etc., be traced back to deviations from Rational Choice standards which are frequently used in economic models, and instead be explained by reference to models of bounded rationality? In order to investigate this question, the dissertation contains both a summary of the history of thought in business cycle theory, as well as an overview of underlying thoughts and applications of theories of bounded rationality and behavioural economics. In particular, literature from cognitive psychology is discussed in this context. The results culminate in a synthesis of business cycle theory and behavioural economics: The influence of individual behavioural characteristics on macroeconomic fluctuations is discussed both on a general theoretical level, as well as through the particular case of a sketch of a behavioural business cycle model.