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In open innovation initiatives for sustainability-oriented innovations, it is indispensable to have a wide array of engaging stakeholders. Yet, as not all relevant actors are able or willing to participate, important opinions can go unnoticed. Due to such stakeholder selection effects, aspects of high relevance may remain uncaptured. To address this issue, we first define the concept of silent stakeholders and relate it to sustainability-oriented innovations. We then discuss the new approach of employing analytical methods to examine existing sources outside the innovation process for silent stakeholder opinions. For this purpose, we conduct an action research study demonstrating how to examine broad discourse data with text analytics for an open innovation project aiming to create a sustainability-oriented innovation. To this end, we develop an approach for the efficient integration of external sources in open innovation processes. We find that text analytics of broad discourse data can particularly support the orientation and idea generation phase for sustainability-oriented innovation. Furthermore, we identify possibilities for the application of further data mining methods to complement open innovation approaches along the innovation process. Building on that, we propose an integrated framework. Hence, we add to the literature on stakeholder participation, analytical methods and innovation management, as well as sustainability-oriented innovation.

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Nowadays, mass customization (MC) is shaped by the application of digital technologies like computeraided design, computer aided manufacturing, and distribution planning. Within a MC process, various data is created, which can be used to gain knowledge about past and future business activities by means of modern data analytics methods. The paper at hand applies design science research and presents a process-based approach for identifying potential analytics use cases for MC. For this purpose, a generic MC process is derived from previous literature and a systematic analysis is carried out using the work systems method. The resulting artifact offers a differentiated view on customers, products, activities, participants, technologies, and information as well as on the information flows within the MC process. It enables manufacturers to identify valuable opportunities for analytics and to optimize current MC processes. Furthermore, it can be used to develop a systematic process for the discovery and evaluation of analytics use cases and novel business models in the future.