Value as a Motivating Factor for Collaboration : The case of a collaborative network for wind asset owners for potential big data sharing

Abstract: The world's need for energy is increasing while we realize the consequences of existing unsustainable methods for energy production. Wind power is a potential partial solution, but it is a relatively new source of energy. Advances in technology and innovation can be one solution, but the wind energy industry is embracing them too slow due to, among other reasons, lack of incentives in terms of the added value provided. Collaboration and big data may possibly provide a key to overcome this. However, to our knowledge, this research area has received little attention, especially in the context of the wind energy industry.   The purpose of this study is to explore value as a motivating factor for potential big data collaboration via a collaborative network. This will be explored within the context of big data collaboration, and the collaborative network for wind asset owners O2O WIND International. A cross sectional, multi-method qualitative single in-depth case study is conducted. The data collected and analyzed is based on four semi-structured interviews and a set of rich documentary secondary data on the 25 of the participants in the collaborative network in the form of 3866 pages and 124 web pages visited.  The main findings are as follows. The 25 participants of the collaborative network were evaluated and their approach to three different types of value were visualized through a novel model: A three-dimensional value approach space. From this visualization clusters of participants resulting in 6 different approaches to value can be distinguished amongst the 25 participants.  Furthermore, 14 different categories of value as the participants express are possible to create through the collaborative network has been identified. These values have been categorized based on fundamental types of value, their dimensions and four value processes. As well as analyzed for patterns and similarities amongst them. The classification results in a unique categorization of participants of a collaborative network. These categories prove as customer  segments that the focal firm of the collaborative network can target.  The interviews resulted in insights about the current state of the industry, existing and future market problems and needs as well as existing and future market opportunities. Then possible business model implications originating from our findings, for the focal firm behind the collaborative network O2O WIND International as well as the participants of the collaboration, has been discussed. We conclude that big data and collaborative networks has potential for value creation in the wind power sector, if the business model of those involved takes it into account. However, more future research is necessary, and suggestions are made.