The Huaiyang Canal, a significant section of the Grand Canal, boasts representative tourist attractions. This study analysis of online reviews from Ctrip and Mahive using R language, Gephi, ROST CM, and SPSS has provided insights into tourists’ perceptions of the Huaiyang Canal’s image. Key findings include: (1) Dominant landscape images encompass gardens, canals, and buildings, emphasizing the historical and cultural assets. Both cultural and natural landscapes equally captivate tourists. (2) The canal’s tourism image perception follows a “garden-history-canal” hierarchy with the canal as the central space and history expanding its tourism features. (3) The perceptions can be categorized into historical and cultural landscapes, man-made projects, and attraction perception. Despite varying tourist numbers in Huaian and Yangzhou, scenic spot experiences are similar. The overall perception of tourists is largely positive, but some express concerns about service attitudes and travel time planning.

The cars industry has undergone significant technological advancements, with data analytics and artificial intelligence (AI) reshaping its operations. This study aims to examine the revolutionary influence of artificial intelligence and data analytics on the cars sector, particularly in terms of supporting sustainable business practices and enhancing profitability. Technology-organization-environment model and the triple bottom line technique were both used in this study to estimate the influence of technological factors, organizational factors, and environmental factors on social, environmental (planet), and economic. The data for this research was collected through a structured questionnaire containing closed questions. A total of 327 participants responded to the questionnaire from different professionals in the cars sector. The study was conducted in the cars industry, where the problem of the study revolved around addressing artificial intelligence in its various aspects and how it can affect sustainable business practices and firms’ profitability. The study highlights that the cars industry sector can be transformed significantly by using AI and data analytics within the TOE framework and with a focus on triple bottom line (TBL) outputs. However, in order to fully benefit from these advantages, new technologies need to be implemented while maintaining moral and legal standards and continuously developing them. This approach has the potential to guide the cars industry towards a future that is environmentally friendly, economically feasible, and socially responsible. The paper’s primary contribution is to assist professionals in the industry in strategically utilizing Artificial Intelligence and data analytics to advance and transform the industry.

The objectives achieved in the Paris Agreement to reduce greenhouse gas emissions and reduce dependence on fossil fuels have caused, in recent years, a growing importance on sustainability in companies in order to reduce Environmental, social and economic impacts. This study is focused on understanding how the variation in West Texas Intermediate crude oil prices affects the Dow Jones Sustainability Index, and therefore the companies included in it, and vice versa. The research aims to examine the statistical properties of both indices, using fractional integration methods, the fractional cointegration vector autoregressive (FCVAR) approach and the continuous wavelet transform (CWT) technique. The results warn of a change in trend, with the application of extraordinary measures being necessary to return to the original trend, while the analysis of cointegration and wavelet analysis measures reflect that an increase in those adopted based on sustainability by the different companies that make up the index imply a drop in the price of crude oil.

The main objective of this article is to analyze the relationship between increases in freight costs and inflation in the markets due to the increases reflected in the prices of the products in some economies in destination ports such as the United States, Europe, Japan, South Africa, the United Arab Emirates, New Zealand and South Korea. We use fractionally integrated methods and Granger causality test to calculate the correlation between these indicators. The results indicate that, after a significant drop in inflation in 2020, probably due to the confinement caused by the pandemic, the increases observed in inflation and freight costs are expected to be transitory given their stationary behavior. We also find a close correlation between both indicators in Europe, the United States and South Africa.

The need for strategic alignment within HR management increased managers’ concern about individual behavior and how this behavior was related to the achievement of goals. In public management, effectively managing employees’ performance has been necessary since Weber’s bureaucratic administration. The individual performance appraisal is the right tool to assess employees’ competencies. Thus, we proposed the following research question: Which factors, as pointed out by theory, have the most significant influence on the individual performance appraisal process? The quantitative method was applied to answer this question, developing and testing a scale via EFA and a hypothetical model via SEM-CB. The results indicated a scale with 25 items able to access the main points of the IPA process and a hypothetical model with 7 constructs that indicate the influence on employee engagement. The main finding is the significant influence of feedback on the whole process. The main theoretical contribution was the construction of the MIPAS scale, and the practical contribution was to identify the points where managers should focus on improving the IPA process with their subordinates.

The telecommunications sector is crucial in a country’s economy. The advancements in information and communication technology have had a significant impact on this sector, particularly in the electronic transactions domain. The utilization of electronic transactions in the telecommunications sector can yield substantial benefits, including increasing non-tax state revenue and economic development in Indonesia. The Covid-19 pandemic has served as a catalyst for the sharp rise in internet usage and telecommunications services, such as work-from-home, distance learning, online shopping or payments, industrial digitization, telemedicine, and others. Consequently, digital transformation has accelerated, necessitating the equitable distribution of Information and Communication Technology (ICT) in Indonesia. The utilization of electronic transactions has directly contributed to the increase in state revenue from non-tax sector, particularly in the telecommunications sector. This can be observed through the continuous growth of non-tax revenue achieved by the Ministry of Communication and Informatics, surpassing the set targets each year in terms of realized value. The objective of this research is to analyze the effectiveness, challenges, and impacts of electronic transactions in increasing non-tax state revenue, in order to generate policy recommendations in Indonesia. This study uses a normative juridical method, analyzing positive legal provisions. Data sources were obtained from three types of legal materials, and data collection was conducted both online and offline. The research results indicate that the utilization of electronic transactions can increase non-tax state revenue in the telecommunications sector through various forms such as telecommunications bill payments, e-commerce transactions, sales of prepaid credit and data packages, telecommunications devices, digital services, content delivery, and transaction monitoring and oversight.