The Experts below are selected from a list of 239730 Experts worldwide ranked by ideXlab platform
Oliver Gassmann - One of the best experts on this subject based on the ideXlab platform.
-
artificial intelligence and Innovation Management a review framework and research agenda
Technological Forecasting and Social Change, 2021Co-Authors: Naomi Haefner, Joakim Wincent, Vinit Parida, Oliver GassmannAbstract:Abstract Artificial Intelligence (AI) reshapes companies and how Innovation Management is organized. Consistent with rapid technological development and the replacement of human organization, AI may indeed compel Management to rethink a company's entire Innovation process. In response, we review and explore the implications for future Innovation Management. Using ideas from the Carnegie School and the behavioral theory of the firm, we review the implications for Innovation Management of AI technologies and machine learning-based AI systems. We outline a framework showing the extent to which AI can replace humans and explain what is important to consider in making the transformation to the digital organization of Innovation. We conclude our study by exploring directions for future research.
-
Towards Systematic Business Model Innovation: Lessons from Product Innovation Management
Creativity and Innovation Management, 2012Co-Authors: Eva Bucherer, Uli Eisert, Oliver GassmannAbstract:Although business model Innovations are decisive for a company's long-term success or failure, they are still poorly understood compared to product Innovations. Thus, their execution is imperfectly supported, and their organizational accountability is insufficiently regulated. In this paper, we systematically investigate similarities and differences between product and business model Innovation to assess the potential of transferring insights and best practices. Therefore, we condense key findings of product Innovation Management into a framework as a basis for the analysis of 11 current cases of business model Innovation. This paper intends to contribute to a better understanding of the options that exist for business model Innovation. We derive implications for an improved Management of business model Innovation based on the cases analysed. For the Innovation process and its organizational anchoring, we disclose potential benefits of a more structured and holistic approach.
Vinit Parida - One of the best experts on this subject based on the ideXlab platform.
-
artificial intelligence and Innovation Management a review framework and research agenda
Technological Forecasting and Social Change, 2021Co-Authors: Naomi Haefner, Joakim Wincent, Vinit Parida, Oliver GassmannAbstract:Abstract Artificial Intelligence (AI) reshapes companies and how Innovation Management is organized. Consistent with rapid technological development and the replacement of human organization, AI may indeed compel Management to rethink a company's entire Innovation process. In response, we review and explore the implications for future Innovation Management. Using ideas from the Carnegie School and the behavioral theory of the firm, we review the implications for Innovation Management of AI technologies and machine learning-based AI systems. We outline a framework showing the extent to which AI can replace humans and explain what is important to consider in making the transformation to the digital organization of Innovation. We conclude our study by exploring directions for future research.
Joakim Wincent - One of the best experts on this subject based on the ideXlab platform.
-
artificial intelligence and Innovation Management a review framework and research agenda
Technological Forecasting and Social Change, 2021Co-Authors: Naomi Haefner, Joakim Wincent, Vinit Parida, Oliver GassmannAbstract:Abstract Artificial Intelligence (AI) reshapes companies and how Innovation Management is organized. Consistent with rapid technological development and the replacement of human organization, AI may indeed compel Management to rethink a company's entire Innovation process. In response, we review and explore the implications for future Innovation Management. Using ideas from the Carnegie School and the behavioral theory of the firm, we review the implications for Innovation Management of AI technologies and machine learning-based AI systems. We outline a framework showing the extent to which AI can replace humans and explain what is important to consider in making the transformation to the digital organization of Innovation. We conclude our study by exploring directions for future research.
Kai-ingo Voigt - One of the best experts on this subject based on the ideXlab platform.
-
Innovation Management lead users and social media introduction of a conceptual framework for integrating social media tools in lead user Management
2014Co-Authors: Markus Ernst, Alexander Brem, Kai-ingo VoigtAbstract:Abstract Purpose With the rise of social media, the practice of Innovation Management is changing rapidly as well. While the opening up of corporate Innovation processes can be observed in literature as well as in practice (commonly known as “Open Innovation”), we draw the reader’s attention to the strategic potential of social media in Innovation Management. For this, a conceptual framework will be introduced. Design/methodology/approach In this chapter, we compare established concepts of knowledge Management to potentials of social media in this field, which offer more efficient and promising ways to integrate external knowledge into Innovation processes. This approach is discussed by considering the integration of customers and especially Lead-Users into corporate product development. Based on the concept of Open Innovation, we reflect the role of Lead-Users in the Innovation process critically. Mounting on our reflections, we show the potentials of social media for integrating Lead-Users and develop a conceptual framework for the integration of Lead-Users using different social media applications. Findings In this paper, a conceptual framework for integrating Lead-Users by using different social media applications is developed and introduced. Originality/value The unique conceptual framework derived in this chapter is enriched with a discussion of the challenges resulting from the implementation of Lead-User integration along with social media in corporate Innovation Management. The chapter can help companies as well as researchers to implement a process for the integration of Lead-Users by using the potentials of social media applications.
-
integration of market pull and technology push in the corporate front end and Innovation Management insights from the german software industry
Technovation, 2009Co-Authors: Alexander Brem, Kai-ingo VoigtAbstract:Abstract Within the framework of this paper, an extensive literature overview of technology and Innovation Management aspects on market pull and technology push will be given. The existing classification of market pull and technology push will be particularly shown and called into question by suggesting a conceptual framework. Additionally, the most common front end Innovation models will be introduced. Finally, the authors will introduce how a technology-based service company is managing the connection of these two alternatives. A special focus will be laid on the accordant methods in order to search for current market needs and new related technologies. The selected case study will focus on one of Germany's biggest and most successful software development and information technology service providers. Based on interviews, document analysis, and practical applications, an advanced conceptual framework will be introduced as to how market pull and technology push activities within the corporate technology and Innovation Management can be integrated. Hence, the purpose of the paper is to introduce a theory-based conceptual framework that can be used in today's corporate environment. In this context, technology managers may use the results as a conceptual mirror, especially regarding the influencing factors of Innovation impulses and the use of interdisciplinary teams (with people from inside and outside the company) to accomplish successful corporate technology and Innovation Management.
Naomi Haefner - One of the best experts on this subject based on the ideXlab platform.
-
artificial intelligence and Innovation Management a review framework and research agenda
Technological Forecasting and Social Change, 2021Co-Authors: Naomi Haefner, Joakim Wincent, Vinit Parida, Oliver GassmannAbstract:Abstract Artificial Intelligence (AI) reshapes companies and how Innovation Management is organized. Consistent with rapid technological development and the replacement of human organization, AI may indeed compel Management to rethink a company's entire Innovation process. In response, we review and explore the implications for future Innovation Management. Using ideas from the Carnegie School and the behavioral theory of the firm, we review the implications for Innovation Management of AI technologies and machine learning-based AI systems. We outline a framework showing the extent to which AI can replace humans and explain what is important to consider in making the transformation to the digital organization of Innovation. We conclude our study by exploring directions for future research.
