As organizations strive to remain competitive in an increasingly dynamic business landscape, the principles of Total Quality Management (TQM) are being reshaped by digital transformation, distributed knowledge and the rising expectations for participation. The present Special Issue, “Crowdsourcing, Open Innovation, and Co-creation for Enhancing Quality and Business,” explores this shifting paradigm through a multidisciplinary lens. The selected papers in this issue bring forward novel frameworks, empirical insights and practical recommendations for how firms and public organizations can enhance quality and performance by engaging broader ecosystems of contributors.The paper by Sboui et al. (2026) investigates initial trust in AI-based chatbots among Generation Z users in Tunisia's telecommunications sector. Their structural equation modeling results highlight that compatibility and social influence enhance trust, while technology anxiety reduces it. Interestingly, perceived ease of use and performance expectancy do not have significant influence. These findings emphasize that successful co-creation with AI systems depends on more than just functionality – it also requires a socio-technical alignment with user expectations and emotional comfort.Two papers explore how gamification and community dynamics can stimulate user engagement on digital platforms. Sharma et al. (2026) apply the DeLone & McLean model and self-determination theory to explore the behavioral outcomes of crowdsourcing within Pokémon Go communities. Their results suggest that system and information quality, combined with intrinsic motivation, drive engagement from consumption to content creation.In parallel, Behl et al. (2026) examine productivity and engagement of gig workers through the lens of media richness and dialogic communication theories. Their results reinforce the role of high-quality, two-way interaction in motivating gig workers, especially when game elements are included. Both papers offer valuable implications for platform designers and digital strategists aiming to maximize engagement quality.Grimaldi et al. (2026) present a systematic literature review that consolidates knowledge on how crowdsourcing supports quality improvement in production and manufacturing processes. This paper fills a critical gap by categorizing the advantages, challenges and potential application domains for organizations seeking to integrate crowdsourcing into their innovation pipelines.Chang et al. (2026) propose a novel DFSS methodology tailored to the insurance sector, combining TRIZ and the Importance–Satisfaction model. Their practical case study demonstrates how new service designs can reduce customer complaints and enhance satisfaction. It serves as a benchmark for structured innovation in service settings.Meanwhile, Jha et al. (2026) explore open-source innovation in the pharmaceutical industry. Their comparative case study of malaria and tuberculosis drug discovery initiatives reveal the nuanced factors influencing successful open design. In resource-constrained and high-impact domains, open innovation offers a promising path for developing quality-driven solutions with societal benefit.Caporuscio et al. (2026) examine smart city infrastructure and propose a dynamic simulation comparing silo-based versus crowdsourced data architectures. Their findings show that crowdsourcing configurations generate more value for app developers and end-users, thereby enhancing the smart city ecosystem.In another public-facing study, the paper by Garcia-Ledezma and Zubieta (2026) on Mexico City's Bus Rapid Transit system illustrates how Twitter enables real-time user participation in service monitoring. Through sentiment and content analysis, the study reveals how digital public feedback loops can drive service quality improvements – a prime example of co-creation in public transportation.Rao et al. (2026) explore how customer-perceived employee competence influences loyalty through justice perception and customer affection in the Indian banking context. Their study adds an important behavioral layer to the quality conversation, demonstrating that emotional and ethical dimensions of service encounters strongly impact long-term loyalty – particularly in rural and underbanked regions.The papers in this Special Issue collectively affirm that crowdsourcing, open innovation and co-creation are no longer experimental ideas but core mechanisms for enhancing quality and competitive advantage. Whether through enabling citizen voice, integrating gig work into innovation workflows or leveraging emotional and trust-based mechanisms in AI and human service channels, the principles of TQM are being extended into participatory, intelligent and dynamic domains.For scholars, this collection provides rich theoretical foundations and empirical paths for future research. For practitioners, it offers actionable insights into designing collaborative and inclusive quality strategies that align with today's complex, digital-first environments.As we look forward, The TQM Journal remains committed to supporting scholarship that bridges theory and practice, innovation and tradition and inclusivity with excellence in quality management.We thank all authors and reviewers for their valuable contributions and insights. Special thanks to the editorial board and the Emerald production team for their support in bringing this issue to fruition.
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