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- International Business Administration Exchange (IBAEx) B.A. (59) (remove)
Companies’ actions towards a Sustainable Supply Chain - A comparative analysis of the food industry
(2020)
The purpose of this bachelor thesis is to describe and critically evaluate the impact of digital marketing on sales and marketing performance overall. For this purpose, this paper uses two main approaches: theoretical and practical. Firstly, starting from the basics of the human communication process, this paper explains the way people communicate with each other and the way it impacted and developed the main marketing channels: both traditional and digital ones, simultaneously outlining the main differences from the communication model’s standpoint. Afterward, the theoretical background section proves the increasing importance of digital marketing in the changing business environment while explaining the main terms and definitions in this area. Lastly, the theoretical part presents the limitations of the traditional marketing funnel, which drove the development of the alternative digital sales funnel, at the same time shaping the KPI's (key performance indicators) to be oriented and the consumer behavior as a whole.
After providing an in-depth theoretical background, the subsequent chapter of this bachelor thesis strives to assess the impact of digital marketing on sales performance based on practical examples. In order to get more prominent and unbiased evidence of digital marketing's effectiveness, I chose three businesses of different sizes and branches, which used digital marketing for diverse purposes. Moreover, each of the three case studies incorporates the interviews of experts. All the invited experts are working or used to work for these companies in marketing-related positions and have extensive knowledge of the marketing strategies being used.
Many fields of science and business are currently undergoing technological changes. Possible future prospects and the impact of our ever increasing reliance on digital algorithms are key factors influencing this field of research. However, only few confront contemporary digitalization with socially unjustified effects. Therefore, this work focuses on the main research question: Can the transparency and fairness concerning the probabilistic distributions of computer based selections be ensured? Or, in contrary, do the current power ranks promote an amplification of bias found in training datasets that swiftly impact marginalized populations at scale. We are still a long way from intellectual and creative thinking computer networks. Our current notion of artificial intelligence (AI) is based on neural networks, which can emit individual "thought processes" based on historical data and homogeneous developer teams. This is not self contained thinking but merely a copy of human thought patterns, which may well be affected by discrimination, e.g. job selection,
credit-ratings, healthcare or other types of personal appraisals. Machine Learning (ML), so far, can not filter out individual human abilities based on historical data and discriminating coding.
This work discusses possible reasons for biased opinions of machine learning classification systems. Also, the social question focusing on gender roles and potential winners and losers through technological changes are explored. Finally, approaches for anti discriminatory use of AI are proposed.