This article explores the possibilities of developing Oman’s tourism sector under China’s Belt and Road Initiative (BRI). Tourism is a cornerstone of Oman’s economy, with the government prioritizing substantial efforts toward its development to foster economic diversification. This paper examines the broader efforts of Oman to strengthen its relations with China, which will indirectly benefit the tourism industry. This article presents a comprehensive analysis of the historical exchanges and future cooperation between China and Oman under BRI, specifically focusing on developing infrastructure and technology in Oman to support the tourism sector. It has been argued that BRI has the potential to significantly contribute to the growth and development of Oman’s tourism sector through increased investment and cooperation with Chinese counterparts.

The primary objective of this research is to investigate how non-financial incentives impact employee motivation within the Small and Medium Enterprises (SMEs) operating in Saudi Arabia. Employing a positivist research approach, we employed a carefully crafted survey to collect data from 365 employees employed by SMEs situated in Jeddah. The study explores various aspects, including the most common non-monetary motivators, the interplay between non-monetary and monetary incentives, and the effects of non-financial incentives on employee engagement, job satisfaction, and commitment. The results of the study indicate that employees working in small and medium-sized enterprises (SMEs) in Saudi Arabia place a significant emphasis on a good work environment, recognition, possibilities for personal and professional development, and career growth as prevalent non-monetary motivators. Additionally, the research illustrates a notable difference in the perceived efficacy of non-financial and financial incentives, whereby non-financial incentives are seen to have an equal, if not greater, impact on both motivation and work satisfaction. Moreover, the study reveals robust positive correlations between non-financial incentives and employee outcomes, underscoring the significance of these incentives in augmenting work satisfaction, job engagement, and commitment. The consequences of employee motivation are influenced by control factors, which have diverse influences, highlighting the complex nature of this phenomenon.

The Consumer Price Index (CPI) is a vital gauge of economic performance, reflecting fluctuations in the costs of goods, services, and other commodities essential to consumers. It is a cornerstone measure used to evaluate inflationary trends within an economy. In Saudi Arabia, forecasting the Consumer Price Index (CPI) relies on analyzing CPI data from 2013 to 2020, structured as an annual time series. Through rigorous analysis, the SARMA (0,1,0) (12,0,12) model emerges as the most suitable approach for estimating this dataset. Notably, this model stands out for its ability to accurately capture seasonal variations and autocorrelation patterns inherent in the CPI data. An advantageous feature of the chosen SARMA model is its self-sufficiency, eliminating the need for supplementary models to address outliers or disruptions in the data. Moreover, the residuals produced by the model adhere closely to the fundamental assumptions of least squares principles, underscoring the precision of the estimation process. The fitted SARMA model demonstrates stability, exhibiting minimal deviations from expected trends. This stability enhances its utility in estimating the average prices of goods and services, thus providing valuable insights for policymakers and stakeholders. Utilizing the SARMA (0,1,0) (12,0,12) model enables the projection of future values of the Consumer Price Index (CPI) in Saudi Arabia for the period from June 2020 to June 2021. The model forecasts a consistent upward trajectory in monthly CPI values, reflecting ongoing economic inflationary pressures. In summary, the findings underscore the efficacy of the SARMA model in predicting CPI trends in Saudi Arabia. This model is a valuable tool for policymakers, enabling informed decision-making in response to evolving economic dynamics and facilitating effective policies to address inflationary challenges.

Urban infrastructures and services—such as public transportation, innovation bodies and environmental services—are important drivers for the sustainable development of our society. How effectively citizens, institutions and enterprises interact, how quickly technological innovations are implemented and how carefully new policies are pursued, synergically determine development. In this work, data related to urban infrastructure features such as patents and recycled waste referred to 106 province areas in Italy are investigated over a period of twenty years (2001–2020). Scaling laws with exponents characterizing the above mentioned features are observed and adopted to scrutinize whether and how multiple interactions within a population have amplification effects on the recycling and innovation performance. The study shows that there is a multiplication effect of the population size on the innovation performance of territories, meaning that the dynamic interactions among the elements of the innovation eco-systems in a territory increase its innovation performance. We discuss how to use such approach and the related indexes for understanding metropolitan development policy.

This work presents a review of Mexican Higher Education during the decade of education for sustainable development and how today it faces the commitments made for the Sustainable Development Agenda 2030. By portraying the agreements that support the UN’s Development Program in advising higher education institutions, the SDGs which can be served through universities and their by-products, the success stories of some universities are shown. This case study addresses the theoretical value of quality of life and harmony of the environment, remarking on how different universities in Mexico have approached this matter as a key part of their curricula, policy, and research. Showcasing a special emphasis given to the work carried out by the University of Sonora, specifically for their institutional practices for sustainability and the study of sustainability from the perspective of Environmental Psychology.

In the face of growing urban problems such as overcrowding and pollution, we urgently need innovative ideas to build smarter and greener cities. Current urban development strategies often fail to address these challenges, revealing a significant research gap in integrating advanced technologies. This study addresses these gaps by integrating green technologies and artificial intelligence (AI), studying its impact on achieving smart and sustainable habitats and identifying barriers to effective use of these technologies, considering local variations in infrastructural, cultural, and economic contexts. By analyzing how AI and green technologies can be combined, this study aims to provide a vision that can be used to improve urban development planning. The results emphasize the significance of environmental responsibility and technological innovation in the development of sustainable urban environments and provide practical recommendations for improving the overall quality of life in cities through planning and urban planning.