Transparency, trust and happiness in chatbot adoption: a multigender analysis from the digital service innovation perspective

Purpose This study examines how technological transparency influences trust, happiness and the intention to use chatbots in digital service environments, integrating perspectives from digital service innovation (DSI) and service-dominant logic (SDL). It additionally analyses gender-based differences to understand perceptual heterogeneity in digital value co-creation processes within emerging economies. Design/methodology/approach A quantitative, cross-sectional study was conducted using a structured online questionnaire administered to users of digital services in the banking, e-commerce and telecommunications sectors. Data were analysed through covariance-based structural equation modelling (CB-SEM) and multigroup analysis (MGA) to assess direct, indirect and gender-differentiated relationships among transparency, trust, happiness and behavioural intention. Findings Transparency was positively associated with trust and happiness, and the two prespecified specific indirect effects linking transparency with usage intention were statistically significant. Because the direct transparency–intention path was non-significant, the full-sample pattern is consistent with indirect-only mediation. Coefficients varied numerically between women and men; however, no formal between-group path-comparison test was conducted, so these variations are interpreted descriptively rather than as confirmed gender effects. Research limitations/implications Convenience sampling, self-reported cross-sectional data and the absence of formal structural-path comparisons limit generalisability and causal or gender-moderation claims. The model also omits established utilitarian predictors from TAM and UTAUT; future research should test whether transparency, trust and happiness add explanatory value beyond perceived usefulness, ease of use, performance expectancy and effort expectancy. Practical implications Organisations should apply Happiness Management and happiness-centred AI design to create transparent, trustworthy and emotionally sustainable chatbot services. Explanations should be concise and layered, with additional detail available on demand, so that transparency supports informed use without creating cognitive fatigue. Personalisation should be guided by monitored user needs rather than assumed gender differences. Social implications The findings highlight transparency as a key support for digital justice and inclusion, particularly in emerging economies where building emotional and cognitive trust is crucial for equitable and sustainable digital transformation. Originality/value The study develops an integrative DSI–SDL account in which transparency functions as a relational resource and happiness represents an affective component of digital value co-creation. Evidence from an emerging economy shows that chatbot adoption involves cognitive-relational and affective mechanisms beyond purely utilitarian evaluations, while gender-group patterns are treated cautiously as descriptive evidence.