OPEN DATA AND INNOVATION ADOPTION: Lessons From Sweden

The Internet has significantly reduced the cost of producing, accessing, and using data, with governments, companies, open data advocates, and researchers observing open data’s potential for promoting democratic and innovative solutions and with open data’s global market size estimated at billions of dollars in the European Union alone (Carrara, Chan, Fischer, & Steenbergen, 2015). This thesis explores the concept of open data, describing and analyzing how open data adoption occurs to better identify and understand key challenges in this process and thus contribute to better use of the available data resources and valuable services for citizens.This research explores the overarching research problem: How does the process of open data adoption occur? Specific research questions include: RQ1: What is the state of open data in terms of political, social, and economic perspectives? RQ2: Who are the main stakeholders utilizing open data; what is their position in the ecosystem, and how do they collaborate? RQ3: Which issues influence open data adoption for open data projects and how? RQ4: What are the potential determinants of open data adoption for open data-driven innovation, and how do these factors influence adoption? To answer these questions, this research has followed an inductive research approach followed by a deductive approach, using both quantitative and qualitative methods.First, this thesis involves macro-level analysis of an open data platform. Second, the thesis maps the open data ecosystem and identifies the ecosystem’s key actors. Third, it determines organizations’ issues and challenges while working with open data and, finally, empirically verifies the factors influencing open data adoption at the organizational level. This research has successfully identified three factors influencing open data adoption—organizational readiness, perceived effort, and perceived benefits—and three that do not (perceived usefulness, perceived risk, and external pressure). Organizational readiness was found to have the greatest influence on open data adoption.The thesis is organized in a hybrid format, meaning it is a monograph with a compilation of studies. The dissertation is structured as follows: First, the introduction defines the open data concept and innovation adoption and explains the reason for this dissertation. Second, the thesis provides an analysis of relevant previous studies, theories, concepts, models, frameworks, and methods. Third, a detailed explanation is given on the methodologies used. Fourth, the empiricalivportion of this thesis comprises four individual studies that constitute the empirical foundations of the research problem. Each study analyzes one research question using its own methodological approach. Fifth, answers to research questions and limitations of this thesis, as well as future research implications, are presented. The conclusion section summarizes this dissertation and its contributions to the areas of open data and innovation adoption.QC 20190128