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This study aims to evaluate an artificial intelligence (AI) capability scale using resource-based theory and tests its impact on dynamic capabilities and organizational creativity to influence the performance of public organizations.

The study used qualitative and quantitative methods to develop and validate an AI capability scale using an integrative psychometric approach. An initial set of 26 items was selected from the literature for qualitative analysis. Self-reported data from 344 public managers in United Arab Emirates public organizations were used for scale refinement and validation. Hypotheses were tested against theoretically related constructs for nomological validation.

A 23-item AI capability scale was developed. Nomological testing confirmed that AI capability positively and significantly enhances dynamic capabilities, which in turn boosts organizational creativity and improves organizational performance.

Previous information system literature has not sufficiently addressed the importance of organizational-level complementary resources in developing distinctive capabilities within public organizations. Grounded in resource-based theory and recent AI research, this study provides a framework for public sector organizations to assess their AI capabilities. The findings empirically support the proposed theoretical framework, showing that AI capability increases dynamic capabilities, organizational creativity and performance.

This study aims to investigate the antecedents of behavioral intention and actual usage of mobile payment (m-payment) services during the COVID-19 pandemic among Indian consumers.

The proposed research model of this study is based on the extended framework of the Unified Theory of Acceptance and Use of Technology (UTAUT2) by using two additional variables, namely, perceived security (PS) and perceived trust (PT). In total, 436 sample respondents are chosen from Indian consumers with experience using m-payment services through the online survey method. The data analysis and proposed hypothetical relationships were tested using confirmatory factor analysis and structural equation modeling techniques.

The results confirm that performance expectancy, effort expectancy, facilitating conditions, PS, PT, habit and price value are antecedents of consumer intention toward adopting m-payment services. Furthermore, behavioral intention significantly influences the actual usage of m-payment services during the COVID-19 pandemic.

Though the impact of COVID-19 has been observed during the research period in getting responses from m-payment service users, the constructs used in the study are confined to the UTAUT2 model, and dimensions related to COVID-19 are not directly included in the measurement scale. The study’s findings propose valuable insights for service providers and policymakers.

This study’s results offer valuable insights to the service providers and policymakers to achieve the Government of India digital India objective of “Faceless, Paperless and Cashless” transactions.

This study’s results contribute to extending the empirical research literature on m-payment as antecedents of behavioral intention toward the adoption of m-payment services during the COVID-19 pandemic. Furthermore, this study assumes important interrelationships among UTAUT2 constructs with the additional incorporation of PS and PT.