On the Cybernetics of Crowdsourcing Innovation: A Process Model

Lin, Lei; Shen, Huawei; Liu, Shenghua; Xu, Lizhen; Cheng, Xueqi

doi:10.1109/access.2022.3154101

Cited by 5 publications

(3 citation statements)

References 43 publications

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“…Crowdsourcing as a tool for open innovation is also explored in terms of public institutions that use crowdsourcing for the public, in order to develop open social innovation (Randhawa et al, 2019). Researchers also propose conceptual models for crowdsourcing innovation from a cybernetics and management perspective (Lin et al, 2022). More and more attention is paid to controlling the flow of knowledge, which is also an aspect of open innovation.…”

Section: Discussionmentioning

confidence: 99%

The impact of crowdsourcing and user-driven innovation on R&D departments’ innovation activity: Application of multivariate correspondence analysis

Szopik-Depczyńska,

Dembińska,

Barczak

et al. 2024

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Research background: In enterprise practices, innovation management is taking on more and more open forms. New, creative sources of inspiration are being sought. More and more companies are opening up to cooperation with external people or entities, thus entering a path of open innovation and crowdsourcing. This development is facilitated by increasingly large numbers of online and virtual communities. The idea is to use the potential of the crowd — collective intelligence and creativity. As the strategy is still developing, knowledge in this area is limited. There is a paucity of research on the impact of crowdsourcing on R&D departments and their innovative activities. Purpose of the article: The study aims to determine whether the use of customer support in the form of crowdsourcing affects the innovative activities of R&D departments that implement user-driven innovation (UDI). Methods: An original questionnaire was used for the study. Fifty-seven R&D departments in Poland participated in the research. A correspondence analysis, performed on the basis of the Burt matrix, was applied for the analysis. The authors also used Cramer's V correlation coefficients. Examination of the acquired correlation coefficients reveals the existence of four distinct categories of enterprises regarding the usage of crowdsourcing and implementation of product innovations, completed R&D projects, employment in R&D departments, and percentage of revenue allocating in R&D works. Findings & value added: Research has shown that R&D departments positively evaluate the effects of using UDI in market research analyses of customer purchasing behavior. It helps to create or improve products or services offered on the market, especially in the field of customization, using the information from national research and development units at the same time. Their purpose is mainly to increase the product range. The findings can help academics and practitioners improve the body of knowledge about the determinants of innovation activity, especially concerning relationships with customers and user-driven innovation practices.

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Section: Discussionmentioning

confidence: 99%

The impact of crowdsourcing and user-driven innovation on R&D departments’ innovation activity: Application of multivariate correspondence analysis

Szopik-Depczyńska,

Dembińska,

Barczak

et al. 2024

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“…Particularly beneficial in the early stages of product development, crowdsourcing aids idea generation and concept development by accessing a wide range of external insights (Lin et al, 2022). Despite its potential, crowdsourcing in new product development is still evolving, and ongoing research aims to determine its efficacy and best practices (Zahay et al, 2018).…”

Section: Literature Review and Hypothesesmentioning

confidence: 99%

Crowdsourcing capabilities: fueling new products? How firm size and business type matter

Dharma Tuah Putra Nasution,

Buana Sari,

Aspan

et al. 2024

Innovative Marketing

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Crowdsourcing has emerged as a valuable tool for organizations seeking to access external knowledge and resources for their innovation processes. This study aims to investigate crowdsourcing capabilities in the context of new product development initiatives, with a focus on exploring the moderating effects of firm size and type. Structural Equation Modeling using Partial Least Squares (SEM-PLS) is used to analyze both the measurement and structural models, with data drawn from 217 owners and managers of diverse businesses in Indonesia. These businesses range from small to medium-scale enterprises across various types, including cafes, restaurants, fashion, culinary, and furniture. The findings reveal a positive and significant impact of crowdsourcing capabilities on new product development initiatives (β = 0.746, p = 0.000). Moreover, the relationship between crowdsourcing and new product development is moderated by firm size (whether small or medium) (β = 0.103, p = 0.045) and the type of business (β = 0.157, p = 0.012). The outcomes of this study are anticipated to enrich the body of knowledge and provide valuable guidance for enterprises seeking to harness crowdsourcing in their new product development processes, with specific factors like firm size and type taken into account. AcknowledgmentThis study was supported by the Indonesian Ministry of Education, Culture, and Technology Research in 2022: Research Grant Scheme “PDUPT”No. 124/LL1/LT/K/2022.

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“…Based on the earlier data gathered by the platform during crowdsourcing, the researchers derive an incentive management approach based on mathematical optimization that executes business processes in a cost-optimal way considering their deadlines [5]. Crowdsourcing is a new business concept which involves different integrations of a job provider, a crowd worker and a crowdsourcing web-based platform, and it describes the existing business model of crowdsourcing and critical analysis for each business model [6]. The lightweight bricks are in high demand in the market.…”

Section: Literature Surveymentioning

confidence: 99%

Secured MCDM Model for Crowdsource Business Intelligence

et al. 2023

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In the current era, there are a plethora of mobile phone companies rendering different features. It is challenging to distinguish the best and create correlations among them. However, this can be accomplished through crowdsourcing. Crowdsourcing is the process of gathering information from multiple sources, and we use the AHP (Analytic Hierarchy Process) process to determine which company’s model is the best among many. The weight value of each model is compared to the assigned values, and if one of the company product weights is greater than the assigned weight, that product is the best. Eventually, we can use this process to select the most preferred and best mobile phone model from among all other models. Gray Relational Analysis (GRA) is one of the most popular models, employing a grey co-efficient that estimates the data items by ranking. This model defines a process’s situation or state as black with no information and white with perfect information. In this work, AHP initially assumes criteria weights and assigns rank with the CR (Consistency Ratio) of 1.5%. The criteria weights are re-assigned based on the outcomes, and the CR remains constant as 1.5%. This work also provides an environmental-based attribute access control system, which adds the strength to the system by providing security and the integrity. So, this proposed work performs as a decision support system combined with the security enhancements, and hence it becomes a complete framework to provide a solution to a target application. The novelty of the proposed work is the combination of the crowdsourcing with the recommender system on a secured framework.

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On the Cybernetics of Crowdsourcing Innovation: A Process Model

Cited by 5 publications

References 43 publications

The impact of crowdsourcing and user-driven innovation on R&D departments’ innovation activity: Application of multivariate correspondence analysis

The impact of crowdsourcing and user-driven innovation on R&D departments’ innovation activity: Application of multivariate correspondence analysis

Crowdsourcing capabilities: fueling new products? How firm size and business type matter

Secured MCDM Model for Crowdsource Business Intelligence

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