Accelerating Innovation Through Analogy Mining

The availability of large idea repositories (e.g., the U.S. patent database) could significantly accelerate innovation and discovery by providing people with inspiration from solutions to analogous problems. However, finding useful analogies in these large, messy, real-world repositories remains a persistent challenge for either human or automated methods. Previous approaches include costly hand-created databases that have high relational structure (e.g., predicate calculus representations) but are very sparse. Simpler machine-learning/information-retrieval similarity metrics can scale to large, natural-language datasets, but struggle to account for structural similarity, which is central to analogy. In this paper we explore the viability and value of learning simpler structural representations, specifically, "problem schemas", which specify the purpose of a product and the mechanisms by which it achieves that purpose. Our approach combines crowdsourcing and recurrent neural networks to extract purpose and mechanism vector representations from product descriptions. We demonstrate that these learned vectors allow us to find analogies with higher precision and recall than traditional information-retrieval methods. In an ideation experiment, analogies retrieved by our models significantly increased people's likelihood of generating creative ideas compared to analogies retrieved by traditional methods. Our results suggest a promising approach to enabling computational analogy at scale is to learn and leverage weaker structural representations.Comment: KDD 201

Crowdsourcing as a way to access external knowledge for innovation

This paper focuses on “crowdsourcing” as a significant trend in the new paradigm of open innovation (Chesbrough 2006; Chesbrough & Appleyard 2007). Crowdsourcing conveys the idea of opening the R&D processes to “the crowd” through a web 2.0 infrastructure. Based on two cases studies of crowdsourcing webstartups (Wilogo and CrowdSpirit), the paper aims to build a framework to characterize and interpret the tension between value creation by a community and value capture by a private economic actor. Contributing to the discussions on “hybrid organizational forms” in organizational studies (Bruce & Jordan 2007), the analysis examines how theses new models combine various forms of relationships and exchanges (market or non market). It describes how crowdsourcing conveys new patterns of control, incentives and co-ordination mechanisms.communauté ; crowdsourcing ; innovation ; formes organisationnelles hybrides ; plateforme ; web 2.0

Reputation Agent: Prompting Fair Reviews in Gig Markets

Our study presents a new tool, Reputation Agent, to promote fairer reviews from requesters (employers or customers) on gig markets. Unfair reviews, created when requesters consider factors outside of a worker's control, are known to plague gig workers and can result in lost job opportunities and even termination from the marketplace. Our tool leverages machine learning to implement an intelligent interface that: (1) uses deep learning to automatically detect when an individual has included unfair factors into her review (factors outside the worker's control per the policies of the market); and (2) prompts the individual to reconsider her review if she has incorporated unfair factors. To study the effectiveness of Reputation Agent, we conducted a controlled experiment over different gig markets. Our experiment illustrates that across markets, Reputation Agent, in contrast with traditional approaches, motivates requesters to review gig workers' performance more fairly. We discuss how tools that bring more transparency to employers about the policies of a gig market can help build empathy thus resulting in reasoned discussions around potential injustices towards workers generated by these interfaces. Our vision is that with tools that promote truth and transparency we can bring fairer treatment to gig workers.Comment: 12 pages, 5 figures, The Web Conference 2020, ACM WWW 202

Identifying new product ideas : waiting for the wisdom of the crowd or screening ideas in real time

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Living Innovation Laboratory Model Design and Implementation

Living Innovation Laboratory (LIL) is an open and recyclable way for multidisciplinary researchers to remote control resources and co-develop user centered projects. In the past few years, there were several papers about LIL published and trying to discuss and define the model and architecture of LIL. People all acknowledge about the three characteristics of LIL: user centered, co-creation, and context aware, which make it distinguished from test platform and other innovation approaches. Its existing model consists of five phases: initialization, preparation, formation, development, and evaluation. Goal Net is a goal-oriented methodology to formularize a progress. In this thesis, Goal Net is adopted to subtract a detailed and systemic methodology for LIL. LIL Goal Net Model breaks the five phases of LIL into more detailed steps. Big data, crowd sourcing, crowd funding and crowd testing take place in suitable steps to realize UUI, MCC and PCA throughout the innovation process in LIL 2.0. It would become a guideline for any company or organization to develop a project in the form of an LIL 2.0 project. To prove the feasibility of LIL Goal Net Model, it was applied to two real cases. One project is a Kinect game and the other one is an Internet product. They were both transformed to LIL 2.0 successfully, based on LIL goal net based methodology. The two projects were evaluated by phenomenography, which was a qualitative research method to study human experiences and their relations in hope of finding the better way to improve human experiences. Through phenomenographic study, the positive evaluation results showed that the new generation of LIL had more advantages in terms of effectiveness and efficiency.Comment: This is a book draf

CROWDSOURCING “BLOCKBUSTER” IDEAS: A DYNAMIC STRUCTURAL MODEL OF IDEATION

Crowdsourcing is becoming an increasing popular tool for new idea generation for firms but the number of ideas generated often decline over time and the implementation rates are very low. Critics of crowdsourcing often attribute these observations to users’ restrictive view about firms’ products leading to contribution of mainly niche ideas, and limited knowledge about firms’ cost structure leading to contribution of mostly infeasible ideas. Using a rich dataset obtained from Ideastorm.com, which is a crowdsourcing website affiliated with Dell, we find that individuals tend to significantly underestimate firm\u27s costs of implementation of their ideas but overestimate the potential of their ideas in the beginning of the their idea contribution history. However, individuals learn very quickly about their abilities to come up with high potential ideas but the learning regarding the firm\u27s cost structure is quite slow. As a result of the learning process, contributors of low potential ideas eventually drop out, and high potential idea contributors remain active

A Consumer-Centric Open Innovation Framework for Food and Packaging Manufacturing

This article has been archived following written permission from IGI Global.Closed innovation approaches have been employed for many years in the food industry. But, this sector recently perceives its end-user to be wary of radically new products and changes in consumption patterns. However, new product development involves not only the product itself but also the entire manufacturing and distribution network. In this paper, we present a new ICT based framework that embraces open innovation to place customers in the product development loop but at the same time assesses and eventually coordinates the entire manufacturing and supply chain. The aim is to design new food products that consumers will buy and at the same time ensure that these products will reach the consumer in time and at adequate quantity. On the product development side, our framework enables new food products that offer an integrated sensory experience of food and packaging, which encompass customization, healthy eating, and sustainability

Prosuming, or when customers turn collaborators: coordination and motivation of customer contribution

This article investigates the phenomenon of increasing integration of customers and users into the organizational creation of value, focusing primarily on the dissolving boundaries between production and consumption. Concepts such as "prosuming", the "working customer", "produsing" and "interactive value creation" have been used to describe this phenomenon. Within the framework of a research project at the Goethe-University Frankfurt/Main, this debate was investigated theoretically as well as empirically in three case studies. The research question is as follows: Why do customers participate in "new types of prosuming" or "interactive value creation" and how are these processes coordinated by the firms? The results show a considerable range of motives and forms of coordination: The customers’ primary motives to voluntarily assume tasks and activities were both intrinsic and extrinsic in nature. The organizational models identified range from strategies of rationalization to prosuming as a basic business model to the collaborative and interactive value creation between the company and the web-community

The role of crowdsourcing cues and relationship norms on customer-brand relationships

Herter, M. M., Shuqair, S., Pinto, D. C., Mattila, A. S., & Zandonai pontin, P. (2023). Does crowdsourcing necessarily lead to brand engagement? The role of crowdsourcing cues and relationship norms on customer-brand relationships. Journal of Product and Brand Management. https://doi.org/10.1108/JPBM-06-2022-4020 --- Funding: This paper received support from the Management of Information Research Center (MagIC), project UIDB/04152/2020, and from the Foundation for Science and Technology (FCT Portugal), project DSAIPA/DS/0113/2019Abstract Purpose This paper aims to examine how the relationship norms established between customers and brands influence customer perceptions of crowdsourcing (vs firm-generated) cues. Design/methodology/approach Four studies (N = 851) examine the moderating role of relationship norms on product labeling cues (crowdsourcing vs firm-generated) effects on brand engagement, and the underlying mechanism of self-brand connection. Findings The findings suggest that crowdsourcing (vs firm-generated) cues lead to higher brand engagement (Studies 1A–1B), mediated by self-brand connection (Studies 2–3). In addition, relationship norms moderate the effects (Study 3), such that under exchange brand relationships crowdsourcing (vs firm-generated) cues yield higher brand engagement, whereas communal brand relationships reverse such effects. Practical implications The findings provide valuable managerial implications by highlighting the importance of using relationship norms as diagnostic cues to successfully implement crowdsourcing initiatives. Originality/value This research adds to the customer-brand relationship literature by revealing an accessibility-diagnosticity perspective of consumers’ reactions to crowdsourcing (vs firm-generated) cues.authorsversionepub_ahead_of_prin