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Participatory Tax Policy Innovation Through Digital Crowdsourcing Platforms

Боҳодир ИсроиловDepartment of Financial analysis, Tashkent State University of Economics, Tashkent, UzbekistanZuhra OtakuzievaTashkent State University of Economics, Tashkent, UzbekistanMamayunis PardaevSamarkand Institute of Economics and Service, Samarkand, UzbekistanBozor Tukhliev0000-0002-4328-3261, TMC Institute, Tashkent, UzbekistanB.Sh. IbragimovDepartment of Taxes and Taxation, Tashkent State University of Economics, Tashkent, UzbekistanUchkun AbduganievDepartment of Financial analysis, Tashkent State University of Economics, Tashkent, Uzbekistan
2025
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Abstract

Participatory tax policy design at the intersection of governance and digital innovation is essential for an improved understanding of citizen engagement in fiscal decision-making. Various crowdsourced participatory tools, for example, idea submission platforms and ranking-based consultation interfaces, could provide structured insights on policy preferences and prioritization with stakeholder traceability and transparency. This study proposes a multi-method evaluation model and semantic integration framework (AHP–SEM–Conceptual Mapping) deployed in Uzbekistan's digital governance context to analyze and interpret these participatory dynamics. In this research, we extract coded responses from taxpayer crowdsourcing forums and then develop a conceptual interaction framework using the Analytical Hierarchy Process method. Our analysis relies on a structural equation model (SEM) construct created from cross-sectional participatory input data. Crowdsourced feedback can be utilized like a collective knowledge system that includes hierarchically weighted factors concurrently utilized and relationally mapped inside a transparent, iterative, and openly accessible policy development environment. We translate these components into a semantic decision map that describes the interactive mechanisms among the crowdsourced variables and how they jointly result in policy innovation outputs. The results show that citizen input weighting has a significant positive impact on both policy legitimacy and adoption feasibility and remains significant after controlling method bias, sample variance, and digital literacy disparities. The presented hybrid model has the potential to strengthen adaptive design of tax policies, allows to quantify the extent of public influence more granularly than traditional consultation formats, and highlights the importance of combined AHP-based weighting and SEM-based causal mapping for inclusive fiscal governance. From a policy-maker's point of view, digital participatory platforms can assist government institutions to make informed and inclusive decisions and help the public sector to institutionalize the participatory tax innovation process.

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