Reining the Power of Big Data: A Study of How Big Data Affects Business Model Development in the Swedish TV-industry

Detta är en D-uppsats från Handelshögskolan i Stockholm/Institutionen för marknadsföring och strategi

Sammanfattning: Companies have always been collecting data, but during recent years technological advancement has allowed them to store and analyze quantities of data that earlier was unimaginable. The age of BIG DATA has come. Big data has reformed how companies look at their market, evaluate their business and analyze their customers. Previously unknown players who rein the power of big data are now disrupting industries and outcompeting legacy players in their own markets. This study looks in to one of these industries, namely the broadcasting industry in Sweden. During recent years the industry has seen disruption from Netflix, a player driven by big data analytics that has forced legacy players to take action and start implementing big data practices. But how will it affect their way of doing business? The aim of the study is to explore the current situation in order to gain an understanding of why it is important for the existing players to implement big data and how it affects their business models. We strive to add to the limited academic research on big data by relating it to business model theories. The research method of choice for this thesis has been a qualitative case study where we have carried out in-depth interviews with representatives from all main legacy broadcasters in the Swedish TV-industry. Business model theory has then been applied to our findings in order to explain the obtained empirical results. Our analysis shows that big data affects the industry to a great extent. With a framework built around business model theories we are able to show that business models can be used as a focal device in order to understand how big data creates value for broadcasters. Three groups of value contributing opportunities were identified in Marketing and CRM, Advertising and Product and Content, as well as the main hindrances to successfully implement big data.

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