Tourism is one of the world's most influential socio-economic sectors, creating jobs, stimulating regional development, and contributing to national economies (Bhatt et al., 2024). As destinations increasingly depend on tourism-driven development, the interdependence among tourism, local society, government systems, and ecosystems has become a central point of scholarly and policy discussion. The conventional method of destination development primarily focuses on infrastructure development, market competitiveness, and tourist numbers. According to Mbaiwa (2003), such an approach has enabled an increasing body of literature to criticise the adverse influence on the local economy, social dynamics, environment, and culture. This is leading to the world of tourism being transformed into new models based on sustainability, community resilience, and responsible governance. Sustainable development of destinations is now aligned with global trends, the first being the United Nations 2030 Sustainable Development Goals (SDGs). According to Sustainable Development Goal SDG 8 (Decent Work and Economic Growth), SDG 12 (Responsible Consumption and Production), and SDG 14/15 (Life Below Water and Life on Land), it is stated that in relation to Tourism. It indirectly promotes SDG 1 (No Poverty), SDG 10 (Reduced Inequalities), SDG 11 (Sustainable Cities and Communities), and SDG 17 (Partnerships). The shift in the field-based measurement of scholarly interest in community well-being, inclusive development, livelihood resilience, environmental stewardship, and more equitable governance is high, indicating that tourism studies are moving much closer to these global sustainability agendas (Krittayaruangroj et al., 2023; Trišić et al., 2023).

Developing countries consider foreign direct investment to be their primary financial resource which also brings new technological advances to their nations, yet researchers are still debating how much technological knowledge foreign direct investment delivers to various regions. The research investigated how foreign direct investment leads to technological advancements in the manufacturing sector of ASEAN member states between 2000 and 2022. The study utilized an autoregressive model with panel lags which analyzed data from ten member countries, including Brunei, Cambodia, Indonesia, Laos, Malaysia, Myanmar, Philippines, Singapore, Thailand and Vietnam. The researchers developed a composite absorptive capacity index through principal components analysis which measured three different components: human capital, information technology infrastructure and institutional quality. The research results demonstrated that foreign direct investment positively impacts labor productivity in the ASEAN manufacturing sector through permanent effects which showed an elasticity coefficient of 0.234 for the complete sample. The relationship between member states and foreign direct investment shows different effects which reach their highest point in upper-middle-income countries with an elasticity of 0.256 and drop to their lowest point in high-income countries which have an elasticity of 0.178. The entire sample showed that absorptive capacity created a positive and significant moderating effect which reached 0.078 for the relationship between foreign investment and productivity. This effect became more powerful in low-income countries which produced a coefficient of 0.112. Granger causality tests demonstrated that foreign investment drives productivity growth while human capital and absorptive capacity enable foreign investment. The supplementary analyses at the manufacturing industry sub-sector level found that the electronics industry achieved 0.312 spillovers while the automobile industry reached 0.278 spillovers and the food industry experienced 0.123 spillovers while the wood industry had 0.078 spillovers. The study establishes that FDI technological spillovers do not occur automatically or uniformly across environments because their implementation depends on three specific factors which include developmental progress and host country absorptive capacity and industrial characteristics. The ASEAN experience shows that foreign investment attraction requires an integrated approach which combines targeted investment incentives with simultaneous education development and research development and institutional quality improvement. Keywords: FDI, Technological Spillovers, Absorptive Capacity, Manufacturing Industry, ASEAN, Labor Productivity.

Trust serves as the most essential non-physical asset which determines e-commerce platform success yet its development process across various cultural settings remains unstudied. The research compared three markets of Uzbekistan and Turkey and Malaysia to identify consumer trust factors which affect e-commerce platforms through multi-group structural equation modeling. The research study included as study participants consumers from three countries who had completed Successful purchases on e-commerce sites. Research used a structured questionnaire to collect data from 1,241 participants who included 412 people from Uzbekistan and 426 people from Turkey and 403 people from Malaysia. The research results demonstrated that all three countries validated the four-dimensional trust model which includes institutional trust seller trust and trust based on others' experience and platform design. The weight of these dimensions varies significantly across countries. In Uzbekistan trust based on others' experiences serves as the strongest trust predictor with a coefficient of 0.41. The trust based on platform design (0.38) and seller characteristics (0.36) function as the primary trust factors in Turkey. In Malaysia users trust platform design (0.42) and institutional trust (0.34) as their main trust sources. The test of measurement invariance confirmed the configuration and metric together with relative scalar invariance maintained their status as invariant measurement elements. Cultural values that individuals hold as their personal beliefs created a major impact on the study while collectivism increased the strength of trust relationships which people formed through their personal experiences with others. All three countries exhibited a strong relationship between trust and repurchase intention which directly linked to e-loyalty. The study shows that trust exists as a universal concept but its development occurs through culturally specific paths which require e-commerce businesses to use localized trust-building methods that match the cultural traits and market development stage of each target market. Platforms that operate in Uzbekistan should implement user feedback systems and electronic word-of-mouth marketing and local influencer partnerships because these strategies provide the most effective way to build consumer trust. Keywords: Consumer Trust, E-Commerce, Cross-Cultural Comparative Analysis, Structural Equation Modeling, Uzbekistan, Turkey, Malaysia.

With the geopolitical and economic pressures between 2022 and 2025, Ukrainian small and medium-sized enterprises (SMEs) used online methods to market their products and services to international markets. This paper analyses how these companies have been able to maintain export business in the face of conflict, displacement and resource limitation. The European Union (EU) and the United States (US) have their performance measured using stratified mixed-method. The quantitative element is a survey of 312 owners or managers of SMEs and the gathering of anonymized performance indicators of Google and Meta advertising campaigns. Qualitative data is obtained in semi-structured interviews with the executives of Ukrainian exporting companies. The study employs a Digital Marketing Capability Index (DMCI), including SEO, PPC advertising, social media, content marketing and analytics, as well as a new WCI to determine the conflict-related constraints. The results show that the ability to operate in digital marketing is an indicator of performance in the foreign markets (𝛽=0.58, p = 0.001). The restrictions created by the war conflict affect this relationship, which points out the weakness of digital tools in a crisis. The Ukrainian SMEs in the EU also have higher returns on advertising and conversion rate as compared to their US counterparts, a trend that can be explained by the fact that they are more geographically and culturally close. It can be seen that SEO is the most effective and long-term digital resource in a limited resource setting. The paper provides empirical evidence in the areas of international marketing and entrepreneurship literature. The recommendations provided in this paper will benefit SME managers, officials advocating digital export programs and other international stakeholders who may be interested in enhancing and empowering the Ukrainian economy using the SME sector as an instrument. Sampling challenges in high-conflict regions limit the study, and the difficulties associated with longitudinal data collection in a rapidly changing environment. Keywords: Digital Resilience, SME Internationalization, Export Competitiveness, Digital Capability, SEO Strategy, Ukraine Conflict Economy

This study examines the dynamics of India’s economy over the past six and a half decades (1960–2024), with a focus on how the USD–INR exchange rate interacts with key factors, including the Consumer Price Index (CPI), lending rates, and the GBP–USD currency rate. To ensure the data was ready for analysis, we applied a range of pre-processing techniques, including log transformations, differencing, and normalisation, followed by stationarity checks using both the Augmented Dickey-Fuller (ADF) and KPSS tests. Authors have compared traditional econometric models such as ARIMA & GARCH with deep learning approaches like LSTM, XGBoost, and LightGBM. To evaluate performance fairly, we used rigorous validation techniques such as walk-forward validation and time-series cross-validation, along with interpretability tools like SHAP, partial dependence plots (PDP), and LIME. The results show that LSTM models significantly outperformed conventional methods, reducing error by 35% (based on RMSE). Among all predictors, CPI proved to be the most influential driver of USD–INR movements. Importantly, the models remained reliable even during periods of major economic turbulence, achieving an out-of-sample R² of 0.783. Key Words: Machine Learning, Time series, ARIMA, LSTM, Hybrid model, GPR, Foreign Exchange

This study aims to examine the impact of generative AI investment information on investment decision quality and investor confidence, while also testing the mediating role of decision quality in this process. With the rapid development of artificial intelligence in the financial sector, generative AI tools can provide real-time, structured, and personalized investment information, potentially influencing investors’ decision-making behavior and psychological confidence. However, empirical research on how AI information improves investment decision quality and subsequently affects investor confidence remains limited. Focusing on investors as the research population, this study collected data through a questionnaire survey. The empirical results indicate that generative AI investment information has a significant positive effect on investment decision quality. In turn, decision quality significantly positively affects investor confidence. At the same time, generative AI investment information also exerts a direct impact on investor confidence and produces an indirect effect through decision quality, highlighting the key mediating role of decision quality between AI information and confidence. Overall, the model demonstrates good fit, and the research hypotheses are supported. Based on the findings, this study provides practical recommendations. Overall, the research not only confirms the value of generative AI investment information in behavioral finance but also offers operationalized scales and application guidelines, contributing significant theoretical and practical insights for fintech development, improved investment decision-making, and the construction of investor psychological confidence. Keywords: Generative AI, Investment Information, Investment Decision Quality, Investor Confidence

Accounting information systems (AIS) are mainly based on computers and software, automating accounting tasks. The application of AIS shows that digitalization has a positive impact on accounting activities. Therefore, using the Unified Theory of Acceptance and Use of Technology (UTAUT2) model and adding the factors of Self-Efficacy and Seamless connectivity to study the accountants' behavioral intention and behavior of using AIS in Vietnam are a suitable research direction, aiming to examine the factors affecting the accountants' behavioral intention and behavior of using AIS, because their behavioral intention and behavior of using AIS can contribute to ensuring the accuracy of accounting data. SEM (Structural Equation Model) model used in this study to analyze and found that the factors Effort Expectancy, Price Value and Cost Saving play a role in promoting and determining the accountants’ behavioral intention of using AIS. At the same time, the factors Habit, Seamless connectivity, Behavioral intentions have positive impacts on the accountants' behavior of using the AIS in Vietnam. The results of this model help accountants and managers have strategies to develop the use of AIS in the increasingly increasing accounting activities in Vietnam. Keywords: Accounting Information Systems, Behavioral Intention, Use Behavior, UTAUT2.

Institutional Theory and Resource-based view explain how the external environment may force businesses to adopt specific practices and how ESG can result in value creation, serving as inspiration for the current study. The Institutional Theory & Resource-based view states that legitimacy, ethics, and productivity are crucial pillars for accomplishing business goals and can lead to creation of resources leading to competitive advantages. Based on these claims, the paper postulated that the ESG Index is less risky, which would indicate that the ESG Index is less volatile. This study is being carried out into two parts. Firstly range-bound volatility estimates viz, ‘Parkinson’, ‘Garman-Klass’, ‘Roger-Satchell’, ‘Yang, and Zhang’ have been used to determine the realised volatility of the Nifty ESG Index across two distinct time horizons and compared with the Nifty 100 to determine the riskiness. Secondly, the volatility dynamics of the Nifty ESG Index was examined for clustering effect using GARCH. The findings show that, in comparison to the Nifty 100, the Nifty ESG 100 Index is more volatile in the long-run but less volatile in the short-run. However, the Nifty ESG Index has shown a moderately strong GARCH effect, indicating persistent volatility and volatility clustering. The findings are compatible with all market phenomena and other research, and they complement one another. Key words- Nifty-ESG, Range-bound volatility estimators, GARCH.

The rapid integration of artificial intelligence (AI) into digital marketing has transformed the way brands communicate with consumers. AI-driven advertising enables personalized, data-driven, and real-time interactions that influence consumer perceptions and engagement. As companies use intelligence more and more to advertise to specific people it is really important to know how artificial intelligence affects what people like and what they buy. Artificial intelligence is a part of digital marketing now and it helps companies understand what people want. This research studied the effects of AI-driven advertising on preferences and purchase decision of consumers. The study was done in New Delhi and by using the convenience sampling method a sample of 1151 respondents was selected for the study. To collect the data Google Docs was used and same was analyzed with the help of SPSS 25.0. For hypothesis testing one sample t-test, ANOVA and chi-square tests were applied. The results of the study indicated that a significant number of consumers were aware of AI-driven advertising and they have also noticed personalized advertisements based on their recent searches. The consumers highlighted the significant positive impact of AI drive advertisements on their perception and purchase decision. Consumers were satisfied with AI-driven advertisements however their satisfaction was highly affected with their perception towards AI-driven advertisements. Key Words: AI-driven advertisements, Consumer preference, Purchase decision

The AS, IAS and IFRS prescribe the procedure to be applied to ensure that the assets of an enterprise are carried at an amount not exceeding their recoverable amount. The standard defines recoverable amount as higher of net realizable value and value in use but if the book value of an asset is less than either of these amount than the asset is not impaired. These standards include only fixed assets for testing of impairment. This paper measures the Impact of Impairment of Assets in select BSE and NSE Listed companies. For this purpose a sample of all BSE and NSE listed companies were taken for the period of 9 years and out of them only 10 companies have made an impairment which is measured in the paper using statistical tool ANOVA and the analysis revealed that 2 independent variables EPS and NP are showing as accounting variables putting the impact on the impairment of the company’s assets and further the Tata Steel Ltd followed by the Oil & Natural Gas Corporations Limited have made the maximum amount of impairment during the period of the study. Keywords: Impairment, Tangible Assets, Intangible Assets, BSE and NSE listed companies.

Purpose: Job satisfaction is an important determinant of teaching effectiveness, institutional performance, and faculty retention in professional education. This study aims to identify the factors influencing job satisfaction among faculty members and evaluate their level of satisfaction. Methodology: A cross-sectional study was conducted among 1,260 faculty members working in professional education institutions in rural and semi-urban areas. Data were collected using a structured Likert-scale questionnaire. Descriptive statistics and multilevel logistic regression analysis were used for data analysis. Findings: The findings indicate that a majority of faculty members were dissatisfied with key job dimensions, particularly work environment, remuneration, and leave policies. Satisfaction levels showed minimal variation across demographic groups, suggesting systemic institutional issues. Practical Implications: The study highlights the need for reforms in professional education institutions, including improved infrastructure, better compensation, and enhanced professional development opportunities

Despite significant socio-economic progress and increased awareness of gender equality, advertising continues to reflect a complex interplay of traditional stereotypes and emerging empowered identities. The research integrates theoretical insights from prior literature with empirical analysis to explore how women are represented and perceived in contemporary media. This study examines the evolving portrayal of women in social advertisements in India and analyses audience perceptions of these changing gender roles. Using Exploratory Factor Analysis (EFA), four key dimensions of women’s portrayal were identified: Traditional Role, Transitional Role, Influential Role, and Progressive Role. The results indicate a gradual shift from conventional depictions of women as dependent homemakers toward more dynamic representations as decision-makers, leaders, and agents of social change. Among these, the Influential Role emerged as the most dominant, highlighting women’s growing impact on family and societal transformation. Further statistical analysis using the Kruskal-Wallis test reveals that gender and educational qualification significantly influence audience perception, whereas social class shows no significant impact. Age demonstrates partial influence, particularly in shaping perceptions of influential and progressive roles. These findings suggest that while societal acceptance of changing gender roles is increasing, variations persist across demographic groups. The study concludes that social advertising plays a crucial role in reshaping societal attitudes by promoting empowered and realistic portrayals of women. While traditional stereotypes have not entirely disappeared, the emergence of progressive narratives indicates a positive shift. Ultimately, the research underscores the potential of media as a catalyst for gender equality, emphasizing the need for more authentic and inclusive representations of women in advertising. Keywords: Women Representation, Social Advertising, Gender Roles, Gender Equality, Perception