CROWDSOURCING-DRIVEN PRODUCT DESIGN AND DEVELOPMENT: A MATHEMATICAL AND EMPIRICAL FRAMEWORK FOR ENHANCING PRODUCT QUALITY IN SMES

Abstract

The manufacturing industry is undergoing a paradigm shift as crowdsourcing emerges as a viable alternative to traditional in-house product design methods. This paper presents a comprehensive framework for integrating crowdsourcing into manufacturing processes, with a focus on improving product design quality in small and medium enterprises (SMEs). A systematic literature review (following PRISMA guidelines) and empirical analyses were conducted to identify key factors influencing product design quality in both conventional and crowdsourced manufacturing settings. We formulated six hypotheses to examine relationships between traditional manufacturing, crowd-based design, and product design quality outcomes. Quantitative validation using statistical models and hypothesis testing indicates that crowdsourcing significantly enhances product design quality across five critical attributes – functionality, reliability, usability, maintainability, and creativity – compared to traditional approaches. We develop a formal mathematical model to represent product design quality as a function of these attributes, and we propose optimization strategies to maximize quality while managing cost and time constraints. The theoretical framework addresses quality control challenges on crowdsourcing platforms and provides practical solutions for manufacturing firms. Synthetic data-driven simulations and comparative analyses show that SMEs leveraging crowdsourcing can access a diverse talent pool, reduce operating costs, and accelerate innovation, all while maintaining high quality standards through rigorous quality management. The proposed integrated framework predicts overall design quality improvements of about 23%, cost reductions of 15–30%, and time-to-market acceleration of 25–40% relative to traditional design methods. This study offers novel insights and mathematical formulations that bridge quality management and crowdsourced manufacturing, yielding both theoretical contributions to applied manufacturing mathematics and actionable guidance for industry practitioners.