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The Kingdom of Saudi Arabia is in the midst of a transformative economic vision, aiming to diversify its economy and reduce dependency on oil revenues. Adopting modern technological solutions like Cloud Accounting Information Systems (AIS) is pivotal in this regard. The purpose of this study is to explore the impact of Cloud AIS on achieving Sustainable Development Goal (SDG) 8.

This study uses a quantitative research strategy and bootstrapping to analyze data from the Kingdom of Saudi Arabia (KSA) industrial sector using partial least squares structural equation modeling.

The study findings provide substantial evidence supporting the positive impact of Cloud AIS on achieving SDG 8. Significant relationships were identified between infrastructure readiness and Cloud AIS utilization, the critical role of data quality in driving Cloud AIS utilization and the significance of security compliance in influencing Cloud AIS utilization. In addition, the quality of service providers was demonstrated to be a crucial factor for effective Cloud AIS implementation. This study also established that infrastructure readiness significantly influences the attainment of SDG 8.

The practical implications of this study provide actionable insights for decision-makers in the KSA industrial sector. Leveraging Cloud AIS effectively will enable organizations to enhance operational efficiencies, promote inclusive economic growth and contribute significantly to achieving SDG 8.

This study contributes significantly to the existing literature by delving into the impact of Cloud AIS on achieving SDG 8, specifically in the context of the KSA – an area that has not been extensively studied.

The Kingdom of Saudi Arabia’s dedicated pursuit of technological modernization positions it as a forefront leader in integrating advanced systems, aligning smoothly with the ambitious goals outlined in Vision 2030. The purpose of this study is to investigate the influence of integrating enterprise resource planning (ERP) and business intelligence (BI) systems on decision-making processes within the industrial sector of Saudi Arabia.

Using a quantitative research design, this study uses a bootstrapping approach and partial least squares structural equation modeling to meticulously analyze data collected from Saudi industrial firms.

The research reveals favorable relationships among infrastructure readiness, data quality, security and access control, user capabilities, user training and the integration of ERP and BI. These positive associations collectively affirm the overarching positive impact of ERP and BI integration on decision-making processes within the industrial sector.

The study underscores the strategic imperative of aligning organizational practices with the identified characteristics to fully unlock the potential benefits of ERP and BI integration in the Saudi Arabian industrial sector.

This study contributes significantly to the existing literature by delving into the integration of ERP and BI in the industrial sector and its nuanced impact on decision-making processes, specifically in the context of the Kingdom of Saudi Arabia – an area that has not been extensively studied.

This research paper aims to explore the concerns and determinants of travelers’ behavior toward ChatGPT in the hospitality and tourism context. It also examines the weight of risk factors versus that of motivation and innovation characteristics influencing travelers’ approach behaviors toward ChatGPT.

A cumulative prospect theory was used to determine travelers’ responses to ChatGPT. This study, using a fuzzy-set qualitative approach, explored risk, motivation and innovation factors as determinants of approach behaviors for ChatGPT.

Findings revealed that risk, motivation and innovation factors were the key triggers of approach behaviors for ChatGPT. An intricate combination effect of the perceived risk, motivation and innovation characteristics was found, and the necessary predictors were determined.

The findings of this study will expand our current knowledge and offer practical insights for the development of ChatGPT in the hospitality and tourism sector.

This study makes a significant contribution to the existing literature by providing a nuanced understanding of the intricate interplay between the various factors that shape customer behavior in the context of technology adoption in hospitality and tourism studies.