Ecosystem data governance as a critical factor for data platform participation

Ecosystem data governance as a critical factor for data platform participation: A BWM approach to determine the relative importance of ecosystem data governance to IoT data providers

de Prieëlle, Fabian (TU Delft Technology, Policy and Management)

de Reuver, G.A. (mentor)
Rezaei, J. (mentor)
Wigboldus, Tijmen (mentor)

Delft University of Technology

Management of Technology (MoT)

2018-12-17

The Internet-of-Things has grown much in popularity over the past years, leading to the gathering of large amounts of pervasive and detailed data. This same trend is seen in the agriculture industry, where a lot of data can be collected on the cultivation methods. The agriculture industry is considered to be a strategically interesting industry for the Internet-of-Things by KPN, the company that commissioned this research. Despite the rapid data collection, businesses rarely exploit the full potential value of their IoT data. One of the methods of value creation with IoT data is to share the data with other parties. Data platform ecosystems make the sharing of data possible, but require the participation from all sides of the platform, especially the data providers, to be successful. Platform sustainability is an important research topic within Information Systems research. However, it remains unsure how the participation of data providers can be ensured. Furthermore, Information Systems researchers have often stressed data governance to have an important role in the success or effectiveness of data platforms. This research aimed to explore how important ecosystem data governance is relative to other relevant factors for the participation willingness of IoT data providers. This knowledge can consequently be used to develop data platforms which IoT data providers are more prone to participate in. Due to the limited time to complete this research, it was decided to focus on the Dutch horticulture sub-sector within agriculture. This sub-sector is considered to be the most advanced Dutch agricultural sub-sector in terms of digitalisation and Internet-of-Things adoption. Relevant factors to data platform participation were identified by means of a literature review. The Best-Worst Method was used in a survey amongst 30 Dutch horticulturists to determine the relative importance of each of the relevant factors. Additionally, six face-to-face semi-structured interviews were conducted to identify concerns related to the relevant factors. The survey results show a low spread of the factors in terms of weight, indicating that Dutch horticulturists do not base their participation decision on just a few decisive factors. Ecosystem data governance is considered around half as important as the most important factor, the benefits of participation, and around three times as important as the least important factor, the external pressure. Although the benefits, human readiness and technological readiness are weighted higher, KPN is recommended to focus on the factors that can be directly influenced by them to direct development time and resources more efficiently. It is therefore recommended to focus on developing a data platform with a high level of security and a low level of complexity. Furthermore, the ecosystem data governance should be another focal factor as appropriate ecosystem data governance can likely eliminate concerns related to several other factors, such as the benefits of participation, safety of data, and the trust in and readiness of other participants. The concerns regarding the misuse of data, unfair distribution of generated value, and the loss of ownership and control over own data, can all be addressed in the ecosystem data governance.

IoT data
Ecosystem data governance
KPN
Data platform
IOS adoption
Inter-Organizational Information Systems
Data sharing
TOE framework
BWM
Best-Worst Method
Agriculture
Horticulture
Ecosystems
Data governance

http://resolver.tudelft.nl/uuid:75870ffb-8938-405c-bd82-ed116204eee4

Student theses

master thesis

© 2018 Fabian de Prieëlle