Kewal Talreja

The current study examines the impact of global financial crises on the capital structure of engineering small and medium enterprises in Pakistan. The study takes GDP as an indicator of financial crises and total debt to total asset ratio, long-term debt to total debt ratio and long-term debt to total asset ratio as indicators of capital structure. The study mainly focuses on panel data from 5 years by including pre and post-crisis periods. The sample size of the study is 20 engineering small and medium enterprises in Pakistan. The research uses inferential statistical techniques to extract results. The findings depict that the financial crises have an insignificant effect on the capital structure of engineering small and medium enterprises in Pakistan. Moreover, by analyzing the statistics, we see that debt financing is frequently decreasing in engineering small and medium enterprises in Pakistan after the occurrence of this financial crisis globally.

There is a growing interest among researchers in analyzing the relationship between fiscal policy and economic growth. The theoretical and empirical studies across many countries have laid groundwork for understanding this emerging phenomenon, providing solid foundation for further exploration of fiscal & economic dynamics. The major justification is given by economic and business analysts who showed inverse relationship between economic growth and fiscal policy. The current analysis evaluated the formulation of different fiscal policies and economic growth based on important variables consisting of government expenditures, tax revenue, and foreign debt. In addition, existing research created a strong connection between economic growth and fiscal policy, has proved to be confusing for the sake of positive and negative approaches. The findings indicate that both tax revenue and government expenditure, have a significant positive impact on economic growth whereas public debt has a significant negative impact on economic growth. These results confirm the effectiveness of fiscal policy on economic growth of Pakistan, highlight the need for policymakers to adopt reliable fiscal measures.

The aim of this research work is to analyze the causal linkage among Pakistan's economic development and the three main financial crisis indicators-interest rates, inflation, and the amount of foreign debt. Additionally, this analysis emphasizes how consistently financial crisis indicators and economic growth. The analysis makes use of sample size covering data from 2000 to 2024. The convergence of equilibrium for series utilized in the work is examined using Johansen's co-integration test. The findings show that the three elements of Pakistan's financial crisis and economic growth have overall causal relationship. The business, economic and each financial crisis indicator taken into consideration in this study have a bidirectional causal relationship, according to estimations based on the pair-wise Granger Causality test. Whereas, the management of economy is determined on the economic and business parameters as analyzed on data which provides a sometimes unidirectional or bidirectional indication for solution of economic crisis and way for economic development.

This study investigates the impact of AI-driven personalization on self-perception, group identity, and social interactions across major social media platforms, including Instagram, Twitter, and YouTube. Utilizing a quantitative approach, data was collected from 500 participants using stratified random sampling to ensure a diverse representation across age, gender, education, and geographic location. The study tests three hypotheses: (H1) AI personalization negatively affects self-perception, increasing anxiety and lowering self-esteem; (H2) personalized content strengthens group identity, leading to greater polarization; (H3) AI reduces social interactions by limiting exposure to diverse viewpoints. Descriptive statistics revealed moderate engagement with personalized content (M = 3.48, SD = 1.12) and notable anxiety (M = 3.26, SD = 1.23). Correlation analysis showed significant negative relationships between personalized content and self-esteem (r = -0.45) and anxiety (r = -0.53), while positive correlations were found between personalized content and in-group bias (r = 0.62). Regression analysis confirmed that personalized content exposure predicted lower self-esteem (? = -0.45), stronger in-group bias (? = 0.62), and reduced interaction with out-groups (? = -0.48). ANOVA results indicated significant differences in anxiety and self-esteem across age groups, with younger participants exhibiting higher anxiety and lower self-esteem. These findings support the hypotheses, showing that AI personalization can negatively affect self-perception, foster group identity, and limit social interactions by curating content that aligns with pre-existing preferences.

This research paper analyses the survey of different contributions in the fields of economics and industrial HRM decisions by taking into account the performance of firms, HRM, advertising expenditures, and areas for the development of organizations or human resources. This study gives a review of existing accounts of literature and the evolution of different firms that reveal the re-examination of early years’ time. This is a serious gap that is not demonstrated by the researchers. It has also been done in different industries for two decades for field existence in influential and academic writers for the rank of economics and economics-based rank and review. This study was mainly done from 2000 to 2022 for the economy of Pakistan. The organizational structure is reviewed, and this paper ends with a brief review of recent developments that have occurred in these decades on the basis of time series econometric modelling.

This research paper determined the analysis of the trade policy of Pakistan by considering the exports and imports values in the provision of different regions on the basis of different times in the context of trade liberalization and trade protective measures, in addition to different core variables such as money supply, government expenditure, and trade openness for annual time series data from 1990 to 2023. This paper also analyzed the workings of the empirical and theoretical bases by considering tariff rates and some statistical analysis for trade theories, reports, and discussions for challenges and opportunities for different trade borders, which may impact the reasons and corners of government policies. In addition to this, the PP test and the ADF test were used for the stationarity of the data. Results were checked with ECM and Granger causality.