IT Support for Intra-Organizational Innovation Networks – An Exploratory Study

The paper examines requirements for IT support in open innovation within companies. Based on an in-depth single-case study, we derive four major levels of IT requirements: incentive & inspiration, information & knowledge, communication & collaboration, and feedback & feed-forward. The multitude of requirements identified on each level clearly points to the need for IT support during the internal open innovation process. The paper concludes that many findings from prior research on innovation management systems apply to the internal open innovation context as well, but with some interesting differences. An IT system for open innovation within a company should pay particular attention to the incentives and inspiration of employees. The system should motivate all employees to participate in open innovation and stimulate innovative ideas by indicating clear benefits as well as recent needs, challenges and developments in their company’s context. Furthermore, a virtual community seems to be a powerful concept for driving open innovation in the company. It fosters the activity of and the interaction between employees, thereby addressing all of our requirement levels. To build and run such an intraorganizational open innovation community, social software offers useful concepts and applications. Based on the identified requirements, we present initial concepts for their implementation

Supporting the Selection of Open Innovation Software Tools

International audienceIn this paper, we present a Web Mining exploratory approach to establish a comparative selection of current Open Innovation (OI) software tools. The starting point of this study is related to " ELLIOT " European project (FP7 ICT) that aims to develop an Internet of Things (IoT) experiential platform involving citizens and users from the early stage of idea creation to the further implementation of innovative IoT applications and services. In this project, one of the objectives is to help the citizens exchanging ideas and co-creating new green services based on environmental data. For this purpose, we develop an exploratory assessment approach based on the QSOS method to elaborate a feature grid in order to support the selection of OI Tools. We find that most of the related works focus on theories about innovation process or product life cycle to classify OI Tools. Our approach combines web mining techniques to finally instantiate the first QSOS reference criteria template dedicated to OI Tools

Leveraging customer knowledge in open innovation processes by using social software

Involving customers in the creation and design process of new products and services has been dis-cussed in practice and research since the early 1980’s. As one of the first researchers, von Hippel (1986) shed light on the concept of Lead Users, a group of users who are able to provide most accu-rate data on future needs for organizations. Subsequently, many scholars emphasized different areas of contribution for customers and how they provide assistance to the process of innovation. First of all, customers may contribute to product innovation (Cooper & Kleinschmidt, 1987; Driessen & Hillebrand, 2013; Füller & Matzler, 2007; Gruner & Homburg, 2000; Sawhney, Verona, & Prandelli, 2005; Snow, Fjeldstad, Lettl, & Miles, 2011; Yang & Rui, 2009) and service innovation (Abecassis-Moedas, Ben Mahmoud-Jouini, Dell’Era, Manceau, & Verganti, 2012; Alam, 2002; Chesbrough, 2011; Larbig-Wüst, 2010; Magnusson, 2003; Paton & Mclaughlin, 2008; Shang, Lin, & Wu, 2009; Silpakit & Fisk, 1985), e.g., by co-creating values (Prahalad & Ramaswamy, 2004), such as concepts or designs as well as reviewing and testing them throughout the stages of the process of innovation. From the customers’ point of view, being involved in innovation processes and becoming a part of the organ-ization is a desire of an increasing number of them. Customers are demanding more individual and more tailored products. They are increasingly knowledgeable and capable of designing and produc-ing their own products and services. Due to the fact that their influence on product development is positively related to the quality of the new product (Sethi, 2000), more and more organizations appreciate them as innovation actors and are willing to pay them for their input. Today, customers are not only involved in the qualification of products (Callon, Méadel, & Rabeharisoa, 2002; Callon & Muniesa, 2005; Grabher, Ibert, & Flohr, 2009) but also allowed to customize and evaluate them on the path to innovation (Franke & Piller, 2004; Piller & Walcher, 2006; von Hippel & Katz, 2002; von Hippel, 2001). Moreover, there is an abundance of studies that stress the customers’ influence on effectiveness (de Luca & Atuahene-Gima, 2007; Kleinschmidt & Cooper, 1991; Kristensson, Matthing, & Johansson, 2008; Still, Huhtamäki, Isomursu, Lahti, & Koskela-Huotari, 2012) and risk (Bayer & Maier, 2006; Enkel, Kausch, & Gassmann, 2005; Enkel, Perez-Freije, & Gassmann, 2005). While the latter comprises the risk of customer integration as well as the customers’ influence on market risks, e.g., during new product development, studies on effectiveness are mostly concerned with customer-orientation and products/services in line with customers’ expectations (Atuahene-Gima, 1996, 2003; Fuchs & Schreier, 2011). The accompanying change in understanding became known as open innovation (OI; first coined by Chesbrough in 2003) and represents a paradigm shift, where organizations switch their focus from internally generated innovation (i.e., ideation, in-house R&D, etc.) toward external knowledge and open innovation processes, thus, allowing them to integrate external ideas and actors, i.e. custom-ers (Chesbrough, 2006) and other external stakeholders (Laursen & Salter, 2006). Since then, OI has been identified as a success factor for increasing customer satisfaction (Füller, Hutter, & Faullant, 2011; Greer & Lei, 2012) and growing revenues (Faems, De Visser, Andries, & van Looy, 2010; Mette, Moser, & Fridgen, 2013; Spithoven, Frantzen, & Clarysse, 2010). In addition to that, by open-ing their doors to external experts and knowledge workers (Kang & Kang, 2009), organizations cope with shorter innovation cycles, rising R&D costs, and the shortage of resources (Gassmann & Enkel, 2004). Parallel to the paradigm shift in innovation, another shift has taken place in information and com-munication technologies (Kietzmann, Hermkens, McCarthy, & Silvestre, 2011). Only a few years ago, when customer integration was still very costly, companies had to fly in customers, provide facilities onsite, permanently assign employees to such activities, and incentivise each task execut-ed by customers. Today, emerging technologies (subsumed under the term ‘social software’) help integrating customers or other external stakeholders, who are increasingly familiar with the such technologies from personal usage experience (Cook, 2008), and grant them access from all over the world in a 24/7 fashion. Examples include blogging tools, social networking systems, or wikis. These technologies help organizations to access customer knowledge, facilitate the collaboration with customers (Culnan, McHugh, & Zubillaga, 2010; Piller & Vossen, 2012) at reduced costs and allow them to address a much larger audience (Kaplan & Haenlein, 2010). On the other hand, customers can now express their needs in a more direct way to organizations. However, each technology or application category may present a completely different benefit to the process of innovation or parts of it and, thus, the innovation itself. Reflecting these developments, organizations need to know two things: how can they exploit the customers’ knowledge for innovation purposes and how may the implementation of social soft-ware support this. Hence, this research addresses the integration of customers in organizational innovation, i.e. new product development. It addresses how and why firms activate customers for innovation and which contribution customers provide to the process of innovation. Additionally, it investigates which tasks customers may take over in open innovations projects and which strategies organiza-tions may choose to do so. It also addresses which social software application supports each task best and how organizations may select the most suitable application out of a rapidly growing num-ber of alternatives. The nature of this research is recommendatory and aims at designing a solution for organizations that are interested in the potential contribution of customers during innovation, already involve customers in innovation tasks or plan to do so. Following the recommendations of this research should result in a more effective organizational exploitation of customer knowledge and their workforce and, thus, a value added to innovation and the outcomes of the process of innovation, e.g., a product that better fits the customers’ expectations and demands or consequently a better adoption of the product by the customer.:1 Introduction 2 Theoretical foundation 3 Research areas and focal points 4 Research aims and questions 5 Methods 6 Findings 7 Conclusion References Essay 1: The Role of External Knowledge in Open Innovation – A Systematic Review of Literature Essay 2: External Knowledge in Organisational Innovation – Toward an Integration Concept Essay 3: Idea Mining – Text Mining Supported Knowledge Management for Innovation Purposes Essay 4: How do Tasks and Technology fit? – Bringing Order to the Open Innovation Chao