A Taxonomy of Web-Based Inbound Open Innovation Initiatives

The term “open innovation” describes the opening of innovation processes of organizations to include external knowledge as well as external paths to market. Various concepts are grouped under the umbrella term “open innovation,” and topics such as crowdsourcing are increasingly receiving attention from researchers as well as practitioners. Unfortunately, the broad coverage and the fact that research on open innovation is a relative young research area also led to a very fragmented usage of the term. In this paper, we seek to contribute to the clarification of the term open innovation, and develop a taxonomy of web-based inbound open innovation initiatives from an organizational perspective. Based on a literature review and the examination of 49 examples we develop a taxonomy consisting of the dimensions process phase, outcome focus, group of participants, knowledge visibility, and facilitation

A Process Model for Crowdsourcing: Insights from the Literature on Implementation

The purpose of the current study is to systematically review the crowdsourcing literature, extract the activities which have been cited, and synthesise these activities into a general process model. For this to happen, we reviewed the related literature on crowdsourcing methods as well as relevant case studies and extracted the activities which they referred to as part of crowdsourcing projects. The systematic review of the related literature and an in-depth analysis of the steps in those papers were followed by a synthesis of the extracted activities resulting in an eleven-phase process model. This process model covers all of the activities suggested by the literature. This paper then briefly discusses activities in each phase and concludes with a number of implications for both academics and practitioners

Data Collaboratives as a New Frontier of Cross-Sector Partnerships in the Age of Open Data: Taxonomy Development

Data collaboratives present a new form of cross-sector and public-private partnership to leverage (often corporate) data for addressing a societal challenge. They can be seen as the latest attempt to make data accessible to solve public problems. Although an increasing number of initiatives can be found, there is hardly any analysis of these emerging practices. This paper seeks to develop a taxonomy of forms of data collaboratives. The taxonomy consists of six dimensions related to data sharing and eight dimensions related to data use. Our analysis shows that data collaboratives exist in a variety of models. The taxonomy can help organizations to find a suitable form when shaping their efforts to create public value from corporate and other data. The use of data is not only dependent on the organizational arrangement, but also on aspects like the type of policy problem, incentives for use, and the expected outcome of data collaborative

Open Innovation Platform Design: The Case of Social Product Development

Open Innovation as a new product development strategy has been used by businesses for decades. However, Social Product Development (SPD) has been recently introduced and popularized as an open innovation business model. The SPD model formalizes and monetizes the collaboration between an organization and creative communities through introducing new products and services. Either managed by intermediaries or directly by innovation sponsors, SPD platforms enable and support online innovative communities to ideate, collaborate, and network. Despite their abilities, many of these platforms do not provide fulfilling user experiences. To bridge this gap, the present study focuses on how SPD platform developers can offer more robust user interfaces (UI) and engaging user experiences (UX) alongside the six key SPD processes—social engagement, ideation, experiential communication, social validation, co-development, and co-commercialization. Building on experience and affordances theories, we offer a design framework that can more broadly inform the design and evaluation of open innovation platforms

What Makes Digital Technology? A Categorization Based on Purpose

Digital technology (DT) is creating and shaping today’s world. Building on its identity and history of technology research, the Information Systems discipline is at the forefront of understanding the nature of DT and related phenomena. Understanding the nature of DT requires understanding its purposes. Because of the growing number of DTs, these purposes are diversifying, and further examination is needed. To that end, we followed an organizational systematics paradigm and present a taxonomic theory for DT that enables its classification through its diverse purposes. The taxonomic theory comprises a multi-layer taxonomy of DT and purpose-related archetypes, which we inferred from a sample of 92 real-world DTs. In our empirical evaluation, we assessed reliability, validity, and usefulness of the taxonomy and archetypes. The taxonomic theory exceeds existing technology classifications by being the first that (1) has been rigorously developed, (2) considers the nature of DT, (3) is sufficiently concrete to reflect the diverse purposes of DT, and (4) is sufficiently abstract to be persistent. Our findings add to the descriptive knowledge on DT, advance our understanding of the diverse purposes of DT, and lay the ground for further theorizing. Our work also supports practitioners in managing and designing DTs