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This study investigates the factors influencing citizen attitudes toward e-government services and their effects on the adoption of e-government services in Saudi Arabia. It sheds light on the moderating role of citizen motivation in the relationship between factors influencing citizen attitudes in favor of e-government services and their adoption and usage behavior in the Saudi Arabian context. The study analyzes both the drivers propelling the uptake and the barriers impeding it.

A descriptive research design was employed in this study, which surveyed 487 respondents from Jeddah and Madina cities and the surrounding region. The research identifies key drivers, including cultural factors, digital literacy, government policy and interventions, privacy and security, technical infrastructure, support services and citizen trust, alongside barriers such as concerns about data security and digital literacy.

The findings reveal the complex interplay of these factors in shaping citizen attitudes toward e-government services and their effects on adoption in Saudi Arabia. The study indicates that citizen motivation toward e-government services moderates the relationship between, adoption and usage behavior.

This study contributes valuable insights for policymakers and practitioners by offering a nuanced perspective on e-government service adoption in the Saudi Arabian context. It enhances our understanding of the factors influencing citizen attitudes and their impact on e-government adoption, highlighting the importance of citizen motivation as a moderating factor in this relationship.

The aim of this study is to examine the behavioral intention (BI) to adopt the Coinbase Wallet by Spanish users.

A survey was administered to individuals residing in Spain between March and April 2021. There were 301 questionnaires analyzed. This research applies a new predictive model based on technology acceptance model (TAM) 2, the unified theory of acceptance and use of technology (UTAUT) model, the theory of perceived risk and the commitment trust theory. A mixed partial least squares structural equation modeling (PLS-SEM)/fuzzy-set qualitative comparative analysis (fsQCA) methodology was employed for the modeling and data analysis.

The results showed that all the variables proposed have a direct and positive influence on the intention to use a Coinbase Wallet. The findings present clear directions for traders, investors and academics focused on improving their understanding of the characteristics of these markets.

First, this study addresses important concerns relating to the adoption of crypto-wallets during the global pandemic. Second, this research contributes to the existing literature by adding electronic word of mouth (e-WOM), trust, web quality and perceived risk as new drivers of the intention to use the Coinbase Wallet, providing unique and innovative insights. Finally, the study offers a solid methodological contribution by integrating linear (PLS) and nonlinear (fsQCA) techniques, showing that both methodologies provide a better understanding of the problem and a more detailed awareness of the patterns of antecedent factors.