274 research outputs found

    Serial Integration, Real Innovation: Roles of Diverse Knowledge and Communicative Participation in Crowdsourcing

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    Despite a burgeoning public and scholarly interest on open innovation and crowdsourcing, how to enable members of online temporary crowd to maintain knowledge integration and innovation remains underexplored. This study seeks to understand the ways in which online crowd members collectively generate more innovative and serial integrative solutions to crowdsourced open innovation challenges. Analyzing 3,200 unique posts generated by 486 participants of 21 organization-sponsored online crowdsourcing innovation challenges, this research demonstrates that crowd members contribute more innovative solutions when being exposed to explicitly shared diverse knowledge, and that crowd members’ communicative participation acts as a catalyst for the production of both innovation and serial knowledge integration. Findings suggest that managers who seek to generate knowledge integration and innovation should endeavor to implement systems that afford high-level communicative participation, as well as encourage crowd members to make their diverse knowledge explicit while minimizing their cognitive load in knowledge sharing

    Pro-socially motivated interaction for knowledge integration in crowd-based open innovation

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    Purpose: The purpose of this paper is to study how the online temporary crowd shares knowledge in a way that fosters the integration of their diverse knowledge. Having the crowd integrate its knowledge to offer solution-ideas to ill-structured problems posed by organizations is one of the desired outcomes of crowd-based open innovation because, by integrating others’ knowledge, the ideas are more likely to consider the many divergent issues related to solving the ill-structured problem. Unfortunately, the diversity of knowledge content offered by heterogeneous specialists in the online temporary crowd makes integration difficult, and the lean social context of the crowd makes extensive dialogue to resolve integration issues impractical. The authors address this issue by exploring theoretically how the manner in which interaction is organically conducted during open innovation challenges enables the generation of integrative ideas. The authors hypothesize that, as online crowds organically share knowledge based upon successful pro-socially motivated interaction, they become more productive in generating integrative ideas. Design/methodology/approach: Using a multilevel mixed-effects model, this paper analyzed 2,244 posts embedded in 747 threads with 214 integrative ideas taken from 10 open innovation challenges. Findings: Integrative ideas were more likely to occur after pro-socially motivated interactions. Research limitations/implications: Ideas that integrate knowledge about the variety of issues that relate to solving an ill-structured problem are desired outcomes of crowd-based open innovation challenges. Given that members of the crowd in open innovation challenges rarely engage in dialogue, a new theory is needed to explain why integrative ideas emerge at all. The authors’ adaptation of pro-social motivation interaction theory helps to provide such a theoretical explanation. Practitioners of crowd-based open innovation should endeavor to implement systems that encourage the crowd members to maintain a high level of activeness in pro-socially motivated interaction to ensure that their knowledge is integrated as solutions are generated. Originality/value: The present study extends the crowd-based open innovation literature by identifying new forms of social interaction that foster more integrated ideas from the crowd, suggesting the mitigating role of pro-socially motivated interaction in the negative relationship between knowledge diversity and knowledge integration. This study fills in the research gap in knowledge management research describing a need for conceptual frameworks explaining how to manage the increasing complexity of knowledge in the context of crowd-based collaboration for innovation

    Essays on Creative Ideation and New Product Design

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    Creative ideation, i.e., the generation of novel ideas, represents the terminus-a-quo in the design and development of innovative products. In my dissertation essays, I examine two approaches employed by firms for creative ideation, (1) channeled ideation, a closed approach, which involves applying replicable patterns or properties observed in historical innovations and (2) idea crowdsourcing, an open approach where firms invite crowds to contribute ideas to solve a specific challenge. In my studies, I clarify how firms can incorporate market-related information in the channeled ideation process and examine how the selection of ideas in crowdsourcing challenges relates to local and global novelty. In Essay 1, “Attribute Auto-dynamics and New Product Ideation,” I introduce a replicable property – attribute auto-dynamics, observed in several novel products, where a product possesses the ability to modify its attributes automatically in response to changing customer, product-system, or environmental conditions. I propose a typology of attribute auto-dynamics, based on an analysis of U.S. utility patents. Based on this typology, I specify a procedural framework for new product ideation that integrates market-pull relevant knowledge and technology-push relevant knowledge. I also illustrate how managers and product designers can apply the framework to identify new product ideas for specific target markets using a channeled ideation approach. In Essay 2, “Selection in Crowdsourced Ideation: Role of Local and Global Novelty,” I examine how the selection of ideas in crowdsourced challenges depends on the form of novelty – local or global. Firms often turn to idea crowdsourcing challenges to obtain novel ideas. Yet prior research cautions that ideators and seeker firms may not select novel ideas. To reexamine the links between idea novelty and selection, I propose a bi-faceted notion of idea novelty that may be local or global. Examining data on OpenIDEO, I find that the selection of novel ideas differs according to the selector, the form of novelty, and the challenge task structure. I also specify a predictive model that seeker firms can leverage when ideator selection metrics such as likes are unavailable.Doctor of Philosoph

    The role of the organizational and operational dimensions in the open collaboration performance: a strategic alignment perspective

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    Purpose –The purpose of this paper is to investigate how the business model and the strategic intent to adopt an open collaboration initiative influence the perceived quality of collaboration outcomes. Design/methodology/approach – This paper presents a framework to analyze the role of the strategic dimension and the operational dimension in open collaboration initiatives through multiple case studies in three companies to understand how the open collaboration initiative was deployed and how was the level of the alignment between these two dimensions.  Findings – The studied cases revealed that when an open collaboration initiative starts in the strategic dimension and there is an alignment between the organizational dimension and operational dimension the collaboration outcomes are clearer and more traceable. Research implications –The study highlights the need to consider the involvement and the internal alignment between strategic and operational dimensions when deploying an open collaboration activity if they want to achieve all the benefits. Practical implications – The presented framework can help managers to evaluate and understand how open collaboration activities are deployed within the company. Social implications – The study shows that when an open collaboration initiative is planned, its results and benefits can be extended to local communities by developing them. Originality/value - This study aims to analyze the open collaboration initiative's contribution to the overall organizational performance through the alignment between the organizational dimension and operational dimension perspective

    Interactive Ideation: Online Team-Based Idea Generation versus Traditional Brainstorming

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    University of Minnesota Ph.D. dissertation. June 2019. Major: Human Factors/Ergonomics. Advisors: Barry Kudrowitz, Stephen Engel. 1 computer file (PDF); vii, 92 pages.Social media and social collaborative platforms are becoming ever more integrated into our lives at all levels. Past research has shown electronic brainstorming and idea generation can be viable options when compared to traditional methods. Building on existing research into the benefits and challenges of ideating through online environments, this study asks if an established collaborative planning platform can be more conducive to generating a high quantity of ideas and high-quality ideas than traditional methods. In this context, the number of ideas generated, the quality of ideas as rated by participants and experts, and group success building upon ideas are evaluated as metrics. The two conditions are compared on performance in an idea generation session. The analysis demonstrated that idea generation through the digital platform Slack, compared to traditional brainstorming, produced more ideas, approximately twice as many high-quality ideas as rated by experts, and nearly twice as much building upon ideas. The results of the study suggest existing online social platforms are viable options for conducting idea generation in small groups and provide an option for collaboration without meeting in person

    Human side of open innovation : review, analysis and recommendations

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    In recent years, open innovation (OI) has emerged as a prominent field of study within management and innovation literature, focusing on the collaborative and open nature of various organizational processes. However, much of the research in this area has been dominated by a firm and technological perspective, with limited attention paid to the human aspects of OI. As such, this thesis aims to address this research gap by conducting a comprehensive review of the OI with focus on human side and individual (micro) perspective. The study involves a systematic review of 54 articles published in top-tier management journals, which are analysed using thematic analysis and content analysis techniques. The review highlights the importance of factors such as trust, communication, collaboration, knowledge sharing, and leadership in facilitating successful OI practices. Moreover, it underscores the critical role of social and cultural factors in shaping the human dynamics of OI. Based on the findings, the thesis proposes research questions that aim to shed further light on the human dimensions around OI, and how they can be leveraged to enhance innovation outcomes. The study contributes to the existing literature by providing a more comprehensive understanding of the role of human factors in OI, and by providing insights that can inform the design of effective OI strategies.Nos últimos anos, a inovação aberta (IA) emergiu como um campo proeminente de estudo na literatura de gestão e inovação, concentrando-se na natureza colaborativa e aberta de vários processos organizacionais. No entanto, grande parte da investigação nesse campo tem sido dominada por uma firma perspetiva tecnológica, com pouca atenção dedicada aos aspetos humanos da IA. Como tal, a presente tese visa colmatar essa lacuna de investigação através da realização de uma revisão abrangente da OI com foco no lado humano e na perspetiva (micro) individual. O estudo envolve uma revisão sistemática de 54 artigos publicados em revistas emblemáticas de gestão, que são analisados usando técnicas de análise temática e de conteúdo. A revisão destaca a importância de fatores como confiança, comunicação, colaboração, compartilhamento de conhecimento e liderança na facilitação de práticas bem-sucedidas de IA. Além disso, enfatiza o papel crítico de fatores sociais e culturais na formação da dinâmica humana da IA. Com base nos resultados, a tese propõe questões de investigação que visam esclarecer as dimensões humanas da IA e como estas podem ser aproveitadas para melhorar os resultados da inovação. O estudo contribui para a literatura existente, fornecendo uma compreensão mais abrangente do papel dos fatores humanos na IA e oferecendo insights que podem informar o design de estratégias eficazes de IA

    Feasibility investigation of crowdsourcing-based product design and development for manufacturing

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    In the era of Industry 4.0, to help manufacturers make quick response to rapidly changing market and customer needs, this research explores the feasibility of realizing benefits of crowdsourcing in product design and development from a lifecycle point of view through investigations on product design quality control and crowdsourcing technology theories, product design lifecycle information modelling, and simulation platform prototyping. It intends to help manufacturers create a product-service ecosystem to deliver values to all involved stakeholders of a PDD process. This study started with building up the theoretical foundation of product design quality control in crowdsourcing design environment. Then, key crowdsourcing technologies for realizing a lifecycle PDD process on a crowdsourcing platform while enabling the design quality were explored. Thirdly, a multi-layer product design lifecycle information model was developed to accommodate all design related information in a PDD process and the identified information at each design phase and the relationships and interactions among information entities were evaluated by case studies and ORM modelling method, respectively. Finally, two crowdsourcing platform prototypes based on the PDLIM were developed to test their effectiveness in communicating design information among stakeholders and delivering value to them. The proposed research made contributions to knowledge through the following improvements/advancements: (1) understanding of key factors affecting product design quality in crowdsourcing design environments, (2) a technical foundation of crowdsourcing technologies for PDD process, (3) a novel product design lifecycle information model accommodating design information in crowdsourcing environments, and (4) guidelines on developing intermediary and integrated crowdsourcing platforms for PDD

    Toward collaborative ideation at scale: Leveraging ideas from others to generate more creative and diverse ideas

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    ABSTRACT A growing number of large collaborative idea generation platforms promise that by generating ideas together, people can create better ideas than any would have alone. But how might these platforms best leverage the number and diversity of contributors to help each contributor generate even better ideas? Prior research suggests that seeing particularly creative or diverse ideas from others can inspire you, but few scalable mechanisms exist to assess diversity. We contribute a new scalable crowd-powered method for evaluating the diversity of sets of ideas. The method relies on similarity comparisons (is idea A more similar to B or C?) generated by non-experts to create an abstract spatial idea map. Our validation study reveals that human raters agree with the estimates of dissimilarity derived from our idea map as much or more than they agree with each other. People seeing the diverse sets of examples from our idea map generate more diverse ideas than those seeing randomly selected examples. Our results also corroborate findings from prior research showing that people presented with creative examples generated more creative ideas than those who saw a set of random examples. We see this work as a step toward building more effective online systems for supporting large scale collective ideation

    Social technologies and collective intelligence

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    Social Technologies and Collective Intelligence is a monograph written by 24 international researchers in the field of Social Technologies and edited by prof. dr. Aelita Skaržauskienė from Mykolas Romeris University in Vilnius, Lithuania. As an academic discipline, social technologies is a highly interdisciplinary research field that focuses on applying existing ICT as well as newly emerging technologies to improve society. This work highlights the dominance of the non-technological social aspect of technology and its interaction with people, emphasizing the institutional power of Collective Intelligence through soft technology. By going through the book, the reader will gain insight and knowledge into the challenges and opportunities provided by this new exciting research field. Scientists will appreciate the comprehensive treatment of the research challenges in a multidisciplinary perspective. Practitioners and applied researchers will welcome the novel approaches to tackle relevant problems in their field. And policy-makers will better understand how technological advances can support them in supporting the progress of society and economy. The book is divided into six parts, each dealing with a well-defined research area at the intersection of Social Technologies and Collective Intelligence. Instead of being split up five ways among particular groups of collaborating authors, each individual author contributes to all five parts of the book their specific knowledge and insights, which makes this monograph a truly collaborative effort and a prime example of collective intelligence

    Same data, different conclusions:Radical dispersion in empirical results when independent analysts operationalize and test the same hypothesis

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    In this crowdsourced initiative, independent analysts used the same dataset to test two hypotheses regarding the effects of scientists’ gender and professional status on verbosity during group meetings. Not only the analytic approach but also the operationalizations of key variables were left unconstrained and up to individual analysts. For instance, analysts could choose to operationalize status as job title, institutional ranking, citation counts, or some combination. To maximize transparency regarding the process by which analytic choices are made, the analysts used a platform we developed called DataExplained to justify both preferred and rejected analytic paths in real time. Analyses lacking sufficient detail, reproducible code, or with statistical errors were excluded, resulting in 29 analyses in the final sample. Researchers reported radically different analyses and dispersed empirical outcomes, in a number of cases obtaining significant effects in opposite directions for the same research question. A Boba multiverse analysis demonstrates that decisions about how to operationalize variables explain variability in outcomes above and beyond statistical choices (e.g., covariates). Subjective researcher decisions play a critical role in driving the reported empirical results, underscoring the need for open data, systematic robustness checks, and transparency regarding both analytic paths taken and not taken. Implications for organizations and leaders, whose decision making relies in part on scientific findings, consulting reports, and internal analyses by data scientists, are discussed
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