University of Oulu

Platforms for big data business models in the healthcare context

Saved in:
Author: Mohamed, Mahmoud1
Organizations: 1University of Oulu, Oulu Business School, Department of Marketing, Marketing
Format: ebook
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 1.2 MB)
Pages: 110
Persistent link:
Language: English
Published: Oulu : M. Mohamed, 2019
Publish Date: 2019-06-12
Thesis type: Master's thesis
Tutor: Ahokangas, Petri
Reviewer: Ahokangas, Petri
Pikkarainen, Minna


The profitability of the business opportunity is defined by the level of owned data and its insights to the business organization. However, the existing literature has not identified how to link between different business models in the data-oriented systems. The previous research efforts focused on the technical aspects of data including data monetization, clustering, and data lifecycle. The purpose of this research is to understand how to link big data and business model thinking in the healthcare context. The main argument of this study provides a novel way to the modularity in the big data business models, which enables the system customers to control the system

Studies show if there is a kind of data-oriented platform that remind patients to do certain tasks (ex. nutrition and medicine reminders) before going to doctors and nurses; the patients would like to use it. In addition, around 90% of the platform users will recommend it to other patients and so on. This pushes the operators in the healthcare industry to transform their traditional human-based data systems into a computer-to-computer system. In the data-intensive systems like the healthcare industry, the value creation is done by monetizing data between system actors to analyze the data and develop extensive knowledge about the end customer. For example, the hospitals have the right to own and anonymize the patient data to ensure the privacy and security of patient information. Then hospitals monetize the patient data with their business partner who has the technical and analytical capability to analyze data. Later, they provide the system with useful insights gained from data analytics.

This is an exploratory phase of research where the qualitative case study approach is applied to examine the possibility of having a common platform for the integrated solutions in the data-oriented systems. To approach these platforms, an empirical study has been conducted over three case companies working in the healthcare context. The data were collected using semi-structured interview discussion. Similar qualitative approaches have been used in some prior studies to examine the value creation in the data-oriented systems and identify the future business models for the digital environments and IoT.

This research contributes to the existing literature by identifying four main platforms for big data business models. The modular platform is done due to the lack of knowledge about the end-customer, it grants system partners the right to control over their platforms. The partnership platform guarantees the continuity of the business process, the Ecosystemic platform gives the end customer the possibility to select what they need from the overall ecosystem. The ownership platform is related to the centralized control over the data source, enabling consistency of the business process.

see all

Copyright information: © Mahmoud Mohamed, 2019. This publication is copyrighted. You may download, display and print it for your own personal use. Commercial use is prohibited.