Data Analytics Platforms: Value Propositions and Adoption Challenges for Small Hospitality Businesses

Managers increasingly seek ways to explore insights from data for business improvements and innovation. Data Analytics (DA) platforms hold promise for businesses, especially small businesses that cannot afford tailor-made proprietary analytics services. DA platforms offer generic analytics features to a pool of businesses, saving costs and...

Toward Business Models for a Meta-Platform: Exploring Value Creation in the Case of Data Marketplaces

Investigating meta-platforms has been a continuing concern within information system literature due to the increasingly complex constellations of platforms in ecologies of ecosystems. A meta-platform is a platform built on top of two or more platforms, hence connecting their respective ecosystems. One promising case to benefit from meta...

Introduction to the Minitrack on Privacy, Trust, and Governance in the Data-driven Economy

The emergence of digital ecosystem governance: An investigation of responses to disrupted resource control in the Swedish public transport sector

Digital ecosystem governance entails the management of complex, dynamic power relationships. As entrant platform providers seek to cultivate an ecosystem, they must carefully navigate these power relationships when dealing with governance tensions. Providers generally seek to leverage the ecosystem's generative potential by facilitating a...

Preparing Future Business Data Sharing via a Meta-Platform for Data Marketplaces: Exploring Antecedents and Consequences of Data Sovereignty

Meta-platforms have received considerable Information Systems scholarly attention in recent years. Meta-platforms enable platform-to-platform openness and are especially beneficial to amplifying network effects in highly-specialized markets. A promising emerging context for applying meta-platforms is data marketplaces—a special type of digital...

It is not (only) about privacy: How multi-party computation redefines control, trust, and risk in data sharing

Firms are often reluctant to share data because of mistrust, concerns over control, and other risks. Multi-party computation (MPC) is a new technique to compute meaningful insights without having to transfer data. This paper investigates if MPC affects known antecedents for data sharing decisions: control, trust, and risks. Through 23...

The Openness of Data Platforms: A Research Agenda

Data platforms are the keystone of the data economy. When opened up, data platforms allow data owners, data consumers and third parties to interact. Yet, openness may also harm business and societal interests. Literature on platform openness does not cover data platforms, and data economy scholars rarely study platform openness. Therefore, this...

The business value of privacy-preserving technologies: the case of multiparty computation in the telecom industry

Purpose: This paper aims to propose a framework for how privacy-preserving technologies (PETs) create business value for organizations. The framework was developed by examining the literature on privacy and information technology’s impact (symbolic and function). The authors evaluate the framework’s applicability using multiparty computation ...