This investigation extends into the intricate fabric of customer-based corporate reputation within the banking industry, applying advanced analytics to decipher the nuances of customer perceptions. By integrating structural equation modeling, particularly through SmartPLS4, we thoroughly examine the interrelations of perceived quality, competence, likeability, and trust, and how they culminate in customer satisfaction and loyalty. Our comprehensive dataset is drawn from a varied demographic of banking consumers, ensuring a holistic view of the sector’s reputation dynamics. The research reveals the profound influence of these constructs on customer decision-making, with likeability emerging as a critical driver of satisfaction and allegiance to the bank. We also rigorously test our model’s internal consistency and convergent validity, establishing its reliability and robustness. While the direct involvement of Business Intelligence (BI) tools in the research design may not be overtly articulated, the analytical techniques and data-driven approach at the core of our methodology are synonymous with BI’s capabilities. The insights garnered from our analysis have direct implications for data-driven decision-making in banking. They inform strategies that could include enhancing service personalization, refining reputation management, and improving customer retention efforts. We acknowledge the need to more explicitly detail the role of BI within the research process. BI’s latent presence is inherent in the analytical processes employed to interpret complex data and generate actionable insights, which are crucial for crafting targeted marketing strategies. In summary, our research not only contributes to academic discourse on marketing and customer perception but also implicitly demonstrates the value that BI methodologies bring to understanding and influencing consumer behavior in the banking sector. It is this blend of analytics and marketing intelligence that equips banks with the strategic leverage necessary to thrive in today’s competitive financial landscape.

Purpose: To reveal the impact mechanism of rural museum intervention on the construction of local identity of rural community residents, and provide practical reference for the protection and utilization of rural cultural identity. Methods: This study takes the Weijiapo Rural Museum in Luoyang, China as the research object, uses participatory observation and in-depth interview methods, and explains the specific characteristics of rural community resident identity construction through identity process theory (IPT). Results: (1) The impact of the intervention of rural museums on rural areas is reflected in four aspects: local spatial reconstruction, transformation of livelihood methods, reconstruction of social relationships, and evolution of cultural customs; (2) under the influence of rural museum construction, the representation of community residents’ identity has shown complex characteristics, with both positive and negative impacts coexisting; (3) the local identity of community residents affects their perception and attitude towards the construction of rural museums.

A method for studying the resilience of energy and socio-ecological systems is considered; it integrates approaches developed at the International Institute of Applied Systems Analysis and the Melentyev Institute of Energy Systems (MESI) of the Siberian Branch of the Russian Academy of Sciences. The article discusses in detail the methods of using intelligent information technologies, in particular semantic technologies and knowledge engineering (cognitive probabilistic modeling), which the authors propose to use in assessing the risks of natural and man-made threats to the resilience of the energy sector and social and ecological systems. More attention is paid to the study and adaptation of the integral indicator of quality of life, which makes it possible to combine these interdisciplinary studies.

Financial inclusion and social protection have been recognised as the primary essential stimuli from the potential they carry as avenues for economic development, especially with respect to reduction in poverty and inequalities, the creation of employment and the enhancement overall welfare and livelihood. However, inclusive access to financial resources and equitable access to social protection interventions have remained a significant concern in Nigeria. In addition, the emergence of the COVID-19 pandemic exposed the weakness of Nigeria in all sectors of the economy such as energy, health, education and food systems and low-level inclusive access to financial resources and social protection coverage. On the other hand, this study argues that financial inclusion and social protection has the potential to mitigation shocks orchestrated by the COVID-19 pandemic. This study empirically examines how social protection interventions and access to financial resources responded to COVID-19 pandemic. The study made use of data sourced from the World Bank’s COVID-19 national longitudinal phone survey 2020 and applied the logit regression. The findings show that social protection and access to financial resources significantly associated with the likelihood of shock mitigation during the COVID-19 pandemic. The results show that social protection intervention reduces the probability of being severely affected by shocks by 0.431. Given this result, the study recommends that the government should put more effort into proper social protection intervention to mitigate the effect of the COVID-19 pandemic.

This study investigates the influence of Environmental, Social, and Governance Disclosures (ESGD) on the profitability of firms, using a sample of 385 publicly listed companies on the Thai Stock Exchange. Data from 2018 to 2022 is sourced from the Bloomberg database, focusing on ESGD scores as indicators of companies’ ESG commitments. The study utilizes a structural equation model to examine the relationships between independent variables; ESGD, Earnings Per Share (EPS), Debt to Assets ratio (DA), Return on Investment Capital (ROIC), Total Assets (TA), and dependent variables Tobin’s Q (TBQ) and Return on Assets (ROA). The analysis reveals a positive relationship between ESGD and TBQ, but not with ROA. Further exploration is conducted to determine if different ESGD levels (high, medium, low) yield consistent effects on TBQ. The findings indicate discrepancies: high and medium ESGD levels are associated with a negative impact on TBQ when EPS increased, whereas low ESGD levels correlate with an increase in TBQ with rising EPS. This nuanced approach challenges the conventional uniform treatment of ESGD in previous research and provides a deeper understanding of how varying commitments to ESG practices affect a firm’s market valuation and profitability. These insights are crucial for firm management, highlighting the importance of ESGD in relation to other financial variables and their effects on market value. This study offers a new perspective on ESGD’s impact, emphasizing the need for differentiated strategies based on ESG commitment levels.

This study investigates the impact of the metaverse on English language teaching, focusing on the perspectives of students from the University of Boyacá. The use of the metaverse was compared with the Moodle platform in a virtual educational environment. A mixed-method approach combining quantitative and qualitative methods was employed. The sample consisted of 30 university students enrolled in English courses, randomly assigned to two groups: one using the metaverse and the other using Moodle. Students’ grades on different activities and assessments throughout the course were collected, and semi-structured interviews were conducted to explore students’ perceptions of the educational platforms. Results revealed that while students recognize the potential of the metaverse to enhance interactivity and learning experience, they also identified technical and accessibility challenges. Although no significant differences in grades were found between the groups, less variability in grades was observed in the metaverse group. The mixed design allowed for a more comprehensive understanding of the impact of the metaverse on English language teaching, while providing a variety of student perspectives on their experience with educational technology. This research contributes to understanding the role of the metaverse in English language teaching and highlights key areas for future research and developments in the field of virtual education.

Border areas can play a crucial role in market integration and infrastructure development between Central Asian countries, thus creating favorable economic growth and regional cooperation conditions. This study aims to assess the economic impact of border areas between Kazakhstan and Uzbekistan, focusing on their role in enhancing market integration and infrastructure development to foster regional growth and cooperation.  Focusing on labor and capital as essential production drivers, this study employs a sophisticated panel data regression model to explore the Cobb-Douglas production function’s application in these border territories. The research findings indicate that regions’ elasticity towards capital and labor inputs vary, necessitating differentiated economic strategies. For capital-intensive areas, we recommend prioritizing investments in infrastructure and technology to boost production outputs. Conversely, in regions where labor significantly influences production, the emphasis should be on human capital development through education, training, and improved labor market conditions. The study’s insights into the evolving trade relations between the two countries underscore the need for flexible economic policies to enhance regional integration and cooperation. This research not only fills a crucial knowledge gap but also offers a blueprint for leveraging the diverse economic landscapes of Central Asia’s border areas in future policy-making and regional economic strategy.

In today’s rapidly evolving world, the integration of artificial intelligence (AI) technologies has become paramount, offering unparalleled value propositions and unparalleled consumer experiences. This study delves into the transformative impact of five AI activities on brand experience and consumer-based brand equity within the retail banking landscape of Lebanon. Employing a quantitative deductive approach and a sample of 211 respondents, the research employs structural equation modeling to analyze the data. The findings underscore the significant influence of four AI marketing activities on brand experience, revealing that factors such as information, accessibility, and customization play pivotal roles, while interaction has a less pronounced effect. Importantly, the study unveils that brand experience acts as a partial mediator between AI marketing activities and consumer-based brand equity. These revelations not only illuminate pathways for retail banks in Lebanon to refine their AI strategies but also underscore the importance of leveraging AI-driven marketing initiatives to bolster customer equity, acquisition, and retention efforts in an increasingly competitive market age.