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    <title language="eng">How AI revolutionizes innovation management – Perceptions and implementation preferences of AI-based innovators</title>
    <abstract language="eng">The application of AI is expected to enable new opportunities for innovation management and reshape innovation practice in organizations. Our exploratory study among 150 AI-savvy innovation managers reveals four different clusters in terms of how organizations may use and implement AI in their innovation management ranging from (1) AI-Frontrunners, (2) AI-Practitioners, and (3) AI-Occasional innovators to (4) Non-AI innovators. The different groups vary not only in their strategy, organizational structure, and skill-building but also in their perceived potential, understanding of the required changes, encountered challenges, and organizational contexts. Our study contributes to a better understanding of the current state of AI-based innovation management, its impact on future innovation practice, and differences in organizations’ AI ambitions and chosen implementation approaches.</abstract>
    <parentTitle language="eng">Technological Forecasting and Social Change</parentTitle>
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    <identifier type="doi">10.1016/j.techfore.2022.121598</identifier>
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      <value>AI-based innovation management Innovation process Organizational setup Organizational context Cluster analysis</value>
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    <title language="eng">The moderating effect of personal features on the consequences of an enjoyable co-creation experience</title>
    <abstract language="eng">Purpose&#13;
This study aims to draw a more nuanced picture of the impact of co-creation experience shedding light on the moderating role of consumers’ personal features. Virtual co-creation is considered a viable strategy to develop consumer-centered products in the digital era. As an additional effect, this research highlighted that co-creation experiences may establish beneficial consumer–brand relationships.&#13;
&#13;
&#13;
Design/methodology/approach&#13;
Using survey data stemming from 727 consumers who virtually engaged in new product development projects, the authors test the hypotheses, applying structural equation modeling.&#13;
&#13;
&#13;
Findings&#13;
The results of this study show that consumers’ personal features such as novelty seeking and dissatisfaction with existing products moderate the impact of an enjoyable experience on aspects of the consumer–company relationship. Consumers’ dissatisfaction with current product solutions is also found to moderate the relationship between an enjoyable co-creation experience and evoked product interest as well as between product involvement and evoked product interest. The study further substantiates previous findings on the relationship-effects of co-creation and particularly highlight the potential of co-creation experiences for nurturing “imaginary” relationships with the product being co-created significantly prior to market launch.&#13;
&#13;
&#13;
Originality/value&#13;
Participants in virtual co-creation approaches are widely heterogeneous individuals ranging from customers and Facebook fans to brand community members and innovative users. The study contributes to a better understanding of how the diversity of the crowd can be handled in virtual co-creation and advances the theory of value co-creation as a new marketing paradigm.</abstract>
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    <title language="eng">Machiavellianism or Morality: Which Behavior Pays Off In Online Innovation Contests?</title>
    <abstract language="eng">Prior research on user behavior in online innovation contests has mainly focused on factors that positively impact prosocial, collaborative behavior, which should ultimately lead to innovative outcomes. However, little is known about the effects of more negative personal characteristics that might result in more competitive, antisocial, and even unethical behavior. This paper considers Machiavellianism as one of the traits that constitute the “dark triad of personality” and explores the relationship between Machiavellianism and participants’ contribution behavior in online innovation contests. Specifically we investigate how Machiavellian characteristics influence individuals’ contribution intensity, communication, and interaction behavior within the contest community as well as the quality and kind of their contributions. This study relies on multisource individual-level data from a large innovation contest in the field of public transportation. We find that the three dimensions of Machiavellianism—distrust of others, amorality, and desire for status—have very distinct behavioral consequences in the context of online innovation contests. Specifically, the oppositional consequences of amoral manipulation and striving for status on the one hand and showing distrust of others on the other hand concerning contribution quantity and contribution quality are found. This study contributes to a deeper understanding of negative personality traits such as Machiavellianism as powerful predictors of behavior and of success within competitive innovation environments and leads to important managerial implications regarding the design and management of innovation contests.</abstract>
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    <title language="eng">The search for innovative partners in co-creation: Identifying lead users in social media through netnography and crowdsourcing</title>
    <abstract language="eng">Despite the extensive literature on the benefits of netnography and crowdsourcing for insight and idea generation, little research has been conducted on their practical relevance and application for identifying lead users. We address this gap through an analysis of 24 lead user projects investigating the viability, underlying processes, and main differences of these new search strategies. We argue that both methods justify the significant investments by additionally providing a user-centric basis for subsequent ideation sessions with lead users. Our findings contribute to user innovation literature by demonstrating new ways of identifying these highly valuable users in the social media age.</abstract>
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    <title language="eng">Innovation analytics: Leveraging artificial intelligence in the innovation process</title>
    <abstract language="eng">Artificial intelligence (AI) is about imbuing machines with a kind of intelligence that is mainly attributed to humans. Extant literature—coupled with our experiences as practitioners—suggests that while AI may not be ready to completely take over highly creative tasks within the innovation process, it shows promise as a significant support to innovation managers. In this article, we broadly refer to the derivation of computer-enabled, data-driven insights, models, and visualizations within the innovation process as innovation analytics. AI can play a key role in the innovation process by driving multiple aspects of innovation analytics. We present four different case studies of AI in action based on our previous work in the field. We highlight benefits and limitations of using AI in innovation and conclude with strategic implications and additional resources for innovation managers.</abstract>
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