Design of architecture principles for a logistics focused, multi-sided data marketplace architecture

In today’s increasingly interconnected and digitized world, the logistics industry plays a critical role in global trade, enabling the seamless movement of goods across essential supply chains (Reinsel et al., 2020). The rapid evolution of digital technologies has led to an unprecedented proliferation of data generated from various aspects of...

The impact of control, trust and risk on business participation in data marketplaces

The adoption of data marketplaces is lacking. Data marketplaces work differently from other information sharing platforms (such as supply chain platforms), because they are more open. This openness allows data to be shared with many more companies, bringing more potential benefits, but also increasing the risk. On data marketplaces there...

Data Marketplace Aggregator: a study towards designing Aggregator Business Models for data marketplaces

The benefit of secondary use of data leads to the belief that data can be monetized through exchanging and trading between businesses. Many new data marketplaces emerge from this, resulting in the heterogeneity of the data marketplace that leads to market fragmentation in the industry. The aggregator business model can offer various values to...

Business-to-Business data sharing via data marketplace meta-platforms: Exploring governance mechanisms to enhance data sovereignty

Modern organisations are increasingly dependent on data to develop new products, services and to improve their operations. However, they are increasingly dependent on external data resources which has led to the rise of data marketplaces where data are traded. This rapid rise of data marketplaces has led to a fragmented data sharing landscape...

Enabling a decentralized architecture for data marketplaces

Data Marketplaces are emerging digital platforms in data management. These platforms enable the infrastructure for data exchange, offering the opportunity for data providers to commercialize their datasets and save time for data consumers in identifying appropriate datasets. Conceptually, data marketplaces provide data exchange services as their...

Multiparty Computation: Identifying the Consumers’ Willingness to Share Sensitive Automotive Data on MPC-­enabled Data Marketplaces: A Discrete Choice Modelling Approach

Over the last several years, the volume of data generated by the Internet of Things (IoT) has expanded at a rapid pace around the world. These often very detailed sensor data could be utilized by many different parties in order to improve services. This same tendency is seen in the automotive sector, where lots of data are gathered by newer and...

Is data really the new oil?: An assessment of the viability of data marketplace business models

Data has often been stated to be “the new oil”. This is said because both oil and data can be very valuable but only after they have been pre-processed. Among other things, a challenge for creating value from data lies in realizing data exchange. This is what data marketplaces aim to do. The number of shutdowns of data marketplaces during the...

Creating a Taxonomy of Business Models for Data Marketplaces

With the amount of available data growing and data posing as a strategic asset to firms, the data economy has started to evolve. Data marketplaces can fulfil a key role in realizing the data economy. The way a data marketplace operates and conducts business can be mapped and managed using a business model. As data marketplaces are a new area of...

Realising platform control in data marketplaces through Secure Multi-Party Computation: A qualitative study exploring the use of Secure Multi-Party Computation (MPC) as an instrument for realising platform control in data marketplaces

Practical problem: In today's digitally transformed and connected world, data has become a critical strategic corporate resource. In this context, data marketplaces are becoming more popular since they enable wider accessibility and more efficient interaction among companies. Despite this, there are several barriers in sharing data through this...

A Business Model Taxonomy for Data Marketplaces: Data Trade in Various Trading Structures

Companies are increasingly reliant on internal and external data sources to innovate their products and services. Currently, companies produce data for their own usage and store it in data silos afterwards. This hinders secondary data usage, when companies reuse external data. Data marketplace owners enable data trade across companies, but...

Effectiveness of Market Segmentation techniques using Data Sharing in the Telecom industry

Since the start of the 21st century, the amount of captured data has been continuously increasing in this digital age. With almost 2.5 quintillion bytes of data being generated and captured every day (Liang et al., 2018), researchers and companies have a strong interest in exploring the value that can be created with this data, called big data...

Enabling Data Marketplaces with Multi-Party Computation (MPC): An Exploratory Study investigating the Implication of the Maturation of Multi-Party Computation (MPC) technology to the Architecture and the Threat Landscape of the Data Marketplaces

The emergence of the Data Marketplaces is the latest iteration in the phenomenon of data-driven transformation of the world. Data marketplaces have emerged as a new form of data-driven business models which enable trading of data between the data owners/providers and data consumers by providing the necessary technological and non-technological...