Open Innovation via Open Source: Collaboration of Companies to Infuse Automobiles with Digital Technologies

Open innovation is a process through which companies open their borders and collaborate with external stakeholders like open source communities to bring new ideas and develop novel digital technologies to gain a competitive position. In this paper, we studied an open source project, i.e., Automotive Grade Linux (AGL) – a Linux Foundation project started by automobile manufacturers and technology companies to innovate technologies for automobiles. By analyzing the code contribution of AGL, we show that much of the code contribution is made by external companies supplying technology to automotive companies and later using the open innovation process to benefit from it. We find evidence that automobile manufacturers engage in open source communities for outside-in, inside-out, and coupled open innovation. As such, this paper shows to managers in larger companies the importance of open source as a way to do open innovation

Unveiling the factors influencing transparency and traceability in agri-food supply chains:an interconnected framework

Purpose: The global food industry is faced with the dilemma of finding a balance between food wastage and food shortage. Approximately one-third of food produced globally goes to waste, while about 800 million people suffer from undernourishment. Given this context, the purpose of this study is to investigate the unresolved challenges related to enhancing transparency associated with products of high perishability and low shelf life. Design/methodology/approach: The authors conducted 25 interviews with global agri-food supply chains (AFSCs) experts to ask what impedes the progress of the current technologies, such as blockchain, to enable transparency and traceability (T&amp;T) in AFSCs. Findings:The findings indicate barriers at the individual, firm and supply chain levels. Based on these barriers, the authors propose an interconnected framework to explain technologically-driven T&amp;T and guide on barrier removal from AFSCs. The authors conclude that by applying technology (i.e. blockchain) the authors can resolve the tension of supporting T&amp;T in AFSCs. This can enable the efficient and transparent tracking of goods, reduction of food waste and loss, as well as promotion of the use of recyclable packaging and further sustainable practices and materials, all of which are aligned with a range of UN Sustainable Development Goals (2, 8, 10 and 12). Moreover, the authors see that some factors are interrelated. Based on these factors, the authors build an interconnected framework to guide on barrier removal from AFSCs. Managers in AFSC would find the findings especially relevant. Originality/value:Drawing on industrial network theory and signalling theory, the authors propose an interconnected framework for explaining barriers (challenges) and potential solutions (opportunities) to T&amp;T in AFSCs. This framework is developed by examining the interconnections of barriers at micro, meso and macro levels and applying signalling theory to explain how solutions address these barriers. The specific contributions of this study are: the list of barriers that impede the implementation of technological solutions for T&amp;T in AFSCs; and a three-stage framework that explains how to remove the barriers for T&amp;T. The study is limited by the focus on blockchain, which calls for future research once the next decentralised technology becomes available.</p

Collaborative Technologies in Automotive and Aerospace Industries towards Industry 4.0

Working in a virtual environment with several dispersed teams becomes an essential part of supply chains, especially for the automotive and aerospace being those industries requiring hundreds of different services and parts manufacturing and assembly. In such scenarios, collaborative technologies support the creation of virtual environments where dispersed teams can jointly respond to business opportunities, and time, cost and travel expenses are reduced. In Industry 4.0, where Information and Communication Technologies (ICT) merge with physical processes, collaborative networks might require additional functionalities. We aim to present an analysis on state-of-the-art tools, technologies and platforms towards assessing its utility for Industry 4.0 in the context of the European Commission Horizon 2020 (EU H2020) programme promoting smart collaborative supply chain systems research. As a first overview, we have identified that it seems to be a lack of a common definition of collaborative technologies and tools, where the concept, applications and characteristics of those is unclear among both industrial and academic fronts. Thus, to present a clear concept of collaborative technologies, this research proposes ontology to represent the formal structure of taxonomy to analyse and classify the collaborative technologies in appropriate categories. This formal structure is also intended to be used later to aid a gap analysis of collaborative technologies, assessing their support and readiness towards Industry 4.0 collaborative networks. The ontology developed is built upon the results of a systematic literature review aimed at finding the definition of collaborative technologies, its features and applications. The systematic review was conducted on extracting relevant articles from the journals proposed by the Association of Information System (AIS) basket of eight

Data sharing for business model innovation in platform ecosystems : from private data to public good

Extant research posits that open data could unlock more than $3 trillion in additional value worldwide across various application domains. This paper investigates a data-sharing perspective in business models of platform ecosystems and discusses how platform owners can derive more value using data. We chose a sample of 12 platforms in which data are used as a key resource for service propositions. By contrasting these cases, we identify and analyse four archetypes: data crawler, data marketplace, data aggregator, and data disseminator. We define the key features of these archetypes and demonstrate how they realise value via the platform. These archetypes can guide managers in realising private and public goods via data sharing. Building on our findings, we derive recommendations for data-driven business model innovation for platform ecosystems