This study looked at how adding augmented reality (AR) to Jordanian fast-food apps during the pandemic impacts brand identity, consumer views, and interactions. It wanted to see if AR strengthens brand connections or leads to brand dilution concerns in the industry. The research utilized a qualitative approach, employing semi-structured interviews with 52 marketing managers from diverse fast-food establishments across Jordan. The study highlighted how mobile apps, especially AR, changed brand interactions in Jordan’s fast-food market. They boosted convenience and engagement but raised worries about food quality and brand dilution due to heavy app use. It stressed the need to balance tech innovation, preserve brand identity, offer personalized experiences, understand user behavior, and tackle app development challenges for better brand loyalty. The research offers practical implications for stakeholders, recommending strategic AR integration, a user-centric approach, cultural sensitivity in tech adoption, and the preservation of emotional connections. It emphasizes the significance of maintaining a delicate balance between leveraging technological advancements and safeguarding the distinctiveness of individual brand identities within an increasingly app-centric landscape. This study uncovers AR’s influence in Jordan’s fast-food scene, highlighting its transformative power and possible drawbacks. It offers practical advice for industry players, guiding them on how to navigate the digital shift without compromising brand integrity or customer connections.

This paper aims to contribute with a literature review on the use of AI for cleaner production throughout industries in the consideration of AI’s advantage within the environment, economy, and society. The survey report based on the analysis of research papers from the recent literature from leading database sources such as Scopus, the Web of Science, IEEE Xplore, Science Direct, Springer Link, and Google Scholar identifies the strategic strengths of AI in optimizing the resources, minimizing the carbon footprint and eradicating wastage with the help of machined learning, neural networks and predictive analytics. AI integration presents vast aspects of environmental gains, including such enhancements as a marked reduction concerning the energy and materials consumed along with enhanced ways of handling the resulting waste. On the economic aspect, AI enhances the processes that lead to better efficiency and lower costs in the market on the other hand, on the social aspect, the application of any AI influences how people are utilized as workers/clients in the community. The following are some of the limitations towards AI adoption as proposed by the review of related literature; The best things that come with AI are yet accompanied by some disadvantages; there are implementation costs, data privacy, as well as system integration that may be a major disadvantage. The review envisages that with the continuation of the AI development in the following years, the optic is going to be the accentuation on the enhancement of the process of feeding the data in real-time mode, IoT connections, and the implementation of the proper ethical approaches toward the AI launching for all segments of the society. The conclusions provide precise suggestions to the people working in the industry to adopt the AI advancements appropriately and at the same time, encourage the lawmakers to create favorable legal environments to enable the ethical uses of AI. This review therefore calls for more targeted partnerships between the academia, industry, and government to harness the full potential of AI for sustainable industrial practices worldwide.

The Mass Rapid Transit (MRT) Purple Line project is part of the Thai government’s energy- and transportation-related greenhouse gas reduction plan. The number of passengers estimated during the feasibility study period was used to calculate the greenhouse gas reduction effect of project implementation. Most of the estimated numbers exceed the actual number of passengers, resulting in errors in estimating greenhouse gas emissions. This study employed a direct demand ridership model (DDRM) to accurately predict MRT Purple Line ridership. The variables affecting the number of passengers were the population in the vicinity of stations, offices, and shopping malls, the number of bus lines that serve the area, and the length of the road. The DDRM accurately predicted the number of passengers within 10% of the observed change and, therefore, the project can help reduce greenhouse gas emissions by 1289 tCO₂ in 2023 and 2059 tCO₂ in 2030.

This study examines the determinants of audit quality and their impact on detecting financial statement fraud at public accounting firms member of OAI Solusi Manajemen Nusantara in Indonesia. Using a quantitative approach, data was collected through a structured questionnaire distributed to auditors and staff. Key findings highlight the significant influence of auditor independence, professional proficiency, and supervision actions on conducting effective audits, thereby enhancing fraud detection capabilities. The research identifies challenges such as the focus on Indonesian firms and potentially limiting broader applicability. Recommendations include enhancing auditor training, adopting stringent audit procedures and technology, and ensuring adherence to auditing standards to improve audit quality and uphold financial reporting integrity. This study underscores the critical role of audit quality in preventing and detecting financial statement fraud, suggesting avenues for future research to explore additional influencing factors.

This study aims to examine the influence of employee and entrepreneur competencies on work efficiency and performance of export companies at the Nong Khai border checkpoint. The research conducted is a quantitative survey. The population for this study includes employees and entrepreneurs from the cross-border export service industry, exporters, and freight forwarder agents operating at the Nong Khai border checkpoint. A non-probability sampling method was employed to select participants. The sample size was Cochran estimated using Cochran’s formula. A structured questionnaire was used to collect data from 385 logistics employees and entrepreneurs selected through purposive sampling. The questionnaires were distributed to employees and entrepreneurs from the export entrepreneurial industry, cross-border export service providers, exporters, and freight forwarder agents at the Nong Khai border checkpoint. The findings revealed that employee and entrepreneur competencies have a direct influence on the work efficiency and performance of export companies. The study concludes that enhancing the competencies of employees and entrepreneurs positively impacts work efficiency and the overall export performance of the company. The research suggests that entrepreneurs should prioritize training and competency development for employees to further improve work efficiency.

This paper examines the impact of the COVID-19 pandemic on financial inclusion in China, a country with a significant agricultural sector and an evolving digital landscape. The pandemic has accelerated the shift towards digital financial services, underscoring disparities in access. This study explores the pre- and post-pandemic scenarios of financial inclusion in China, evaluates the economic and social impacts of the pandemic, and assesses the role of digital transformation in the financial sector. It also investigates the changing roles of commercial banks and microfinance institutions, the integration of technology in finance, and the development of rural-urban economic linkages. The paper aims to propose strategies to enhance financial inclusion, ensuring it reaches the most vulnerable, and concludes with recommendations for creating a more equitable and robust economic system.