Pakistan is a leading emerging market as per the recent classification of the International Monetary Fund (MF), and hedging is used as a considerable apparatus for minimizing a firm’s risk in this market. In these markets, investors are customarily unaware about the hedging activities in firms, due to the occupancy of asymmetric environment prevailing in firms. This research paper adds a new insight and vision to the existing literature in the field of behavioral finance by examining the impact of hedging on investors’ sentiments in the presence of asymmetric information. For organizing this research, 366 non-financial firms are taken up as the size sample; all these firms are registered in the Pakistan Stock Exchange. A two-step system of generalized method of moments (GMM) model is implemented for regulating the study. The findings of empirical evidence exhibit that there is a positive relationship between investors’ sentiments and hedging. Investors’ sentiments are negative in relationship with asymmetric information. Due to the moderate presence of asymmetric information, hedging is positively related to investors’ sentiments although this relation is non-significant.
First principles simulation studies using the density functional theory have been performed on (9, 0) Zigzag Singlewalled Carbon Nanotube (SWCNT) to investigate its electronic, optical and thermodynamic properties using CASTEP (Cambridge Sequential Total Energy Package) and DFTB (Density Functional based Tight Binding) modules of the Material Studio Software version 7.0. Various functionals and sub-functionals available in the CASTEP Module (using Pulay Density Mixing treatment of electrons) and various eigen-solvers and smearing schemes available in the DFTB module (using smart algorithm) have been tried out to chalk out the electronic structure. The analytically deduced values of the band gap obtained were compared with the experimentally determined value reported in the literature. By comparison, combination of Anderson smearing scheme and standard diaogonalizer produced best results in DFTB module while in the CASTEP module, GGA (General Gradient approximation) functional with RPBE (Revised-perdew-Burke-Ernzerh) as Sub-functional was found to be the most consistent. These optimized parameters were then used to determine various electronic, optical and thermodynamic properties of (9, 0) Singlewalled Nanotube. (9, 0) Singlewalled Nanotube, which is extensively being used for sensing NH3, CH4 & NO2, has been picked up in particular as it is reported to exhibit a finite energy band gap in contrast to its expected metallic nature. The study is of utmost significance as it not only probes and validates the simulation route for predicting suitable properties of nanomaterials but also throws light on the comparative efficacy of the different approximation and rationalization quantum mechanical techniques used in simulation studies.
In the Fourth Industrial Revolution (4IR) era, the rapid digitalisation of services poses both opportunities and challenges for the banking sector. This study addresses how adopting artificial intelligence (AI) and online and mobile banking advancements can influence customer satisfaction, particularly in Kaduna State, Nigeria. Despite significant investments in AI and digital banking technologies, banks often struggle to align these innovations with customer expectations and satisfaction. Using Structural Equation Modeling (SEM), this research investigates the impact of customer satisfaction with online banking (C_O) on AI integration (I_A) and mobile banking convenience (C_M). The SEM model reveals that customer satisfaction with online banking significantly influences AI integration (path coefficient of 0.40) and mobile banking convenience (path coefficient of 0.68). These results highlight a crucial problem: while technological advancements in banking are growing, their effectiveness is highly dependent on customer satisfaction with existing digital services. The study underscores the need for banks to prioritise enhancing online banking experiences as a strategic lever to improve AI integration and mobile banking convenience. Consequently, the research recommends that Nigerian banks develop comprehensive frameworks to evaluate and optimise their technology integration strategies, ensuring that technological innovations align with customer needs and expectations in the rapidly evolving digital landscape.
This study addresses the impact of the tourism sector on poverty, poverty depth, and poverty severity in Indonesia, focusing on the micro-level dynamics in the province. Despite numerous tourism destinations, their strategic contribution to regional progress remains underexplored. The motivation stems from the need to comprehend the nuanced relationship between tourism and poverty at both the national and local levels, with specific attention to the untapped potential at the province level in Indonesia. We hypothesize that a higher tourism sector GRDP will be inversely correlated with poverty levels, and the inclusion of a Covid-19 variable will reveal a structural impact on poverty dynamics. Employing a Panel Regression Model, secondary data from the Central Statistics Agency (BPS) spanning 2011–2020 is utilized. A panel data regression equation model, including CEM, FEM, and REM, is employed to analyze the intricate relationship between tourism and poverty. The findings demonstrate a negative correlation between higher tourism sector GRDP and the number of poor people. The Covid-19 variable, considered a structural break, reveals a significant association between increased cases and elevated poverty and severity across Indonesian provinces. This study contributes a micro-level analysis of tourism’s role, emphasizing its impact at the provincial level. The findings underscore the need for strategic initiatives to harness the untapped potential of tourism in alleviating poverty and promoting regional progress.
Countries employ various strategies to strengthen their soft power through education, public campaigns, mandatory service, and community involvement, essential for building a well-informed, prepared, and resilient citizenry. In Indonesia, the Civic Awareness for State Defence (CASD) program is designed to instil state defence awareness among citizens. This study introduces the Indonesia State Defence Index (SDI), a novel metric grounded in theoretical constructs such as national identity, nationalism, patriotism, and national pride. Differentiating from previous indices, our SDI employs advanced methodologies including Principal Component Analysis (PCA) and Structural Equation Modeling (SEM) to enhance measurement accuracy. Unlike earlier approaches that used traditional aggregation methods, our use of PCA ensures the reduction of dimensions for each state defence indicator, thereby guaranteeing that only the intended dimensions are measured. Utilising data from the State Defence Survey conducted by the Indonesian Ministry of Defence from 1 March to 26 June 2024, we aim to measure and benchmark SDI values across Indonesian regions, thereby elucidating the civic awareness profile in the context of state defence. The refined SDI provides critical insights for policymakers, highlighting regions that require focused interventions to bolster state defence preparedness.
As the aging trend intensifies, the Chinese government prioritizes technological innovation in smart elderly care services to enhance quality and efficiency, catering to the diverse needs of the elderly. This study examines the acceptance and usage behavior of smart elderly care services among elderly individuals in Xi’an, using a modified Unified Theory of Acceptance and Use of Technology (UTAUT) model that includes digital literacy as a moderating variable. Data were collected via a survey of 299 elderly individuals aged 60 and above in Xi’an. The study aims to identify factors influencing the acceptance and usage behavior of smart elderly care services and to understand how digital literacy moderates the relationship between these factors and usage behavior. Regression analysis assessed the direct effects of Performance Expectancy (PE), Effort Expectancy (EE), Social Influence (SI), and Facilitating Conditions (FC) on usage behavior. These dimensions were then integrated into a comprehensive index Service Acceptance to evaluate their overall impact on usage behavior, with behavioral intention examined as a potential mediating variable. Results indicate that EE and SI significantly impact the adoption of smart elderly care services, whereas PE and FC do not. Behavioral intention mediates the relationship between these variables and usage behavior. Additionally, gender, age, and digital literacy significantly moderate the impact of service acceptance on usage behavior. This study provides valuable theoretical and practical insights for designing and promoting smart elderly care services, emphasizing the importance of usability and social promotion to enhance the quality of life for the elderly.
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