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Author: search.filters.author.Khan, Majid

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    Human Resource Development and Enhancement of Core Competencies for Sustainable Agro Tourism Community Enterprises: A Creative Economy Perspective
    (2026-06-01)
    Rodjam, Chumpon
    ;
    Chanthakit, Panyada
    ;
    Chotianusorn, Eakolarn
    ;
    Asavapatra, Pachoke Lert
    ;
    Janmuangthai, Wutipong
    This study investigates the role of Human Resource Development (HRD) and enhancement of core competencies in promoting the sustainability and competitiveness of agro-tourism community enterprises in Thailand. Utilizing a quantitative method design, data were collected from 265 participants using structured questionnaires and interviews. The study employed confirmatory factor analysis (CFA) and structural equation modeling (SEM) to examine the relationships among variables. Results indicated that HRD significantly influenced both the enhancement of core competencies (β = 0.53, p < 0.001) and enterprise sustainability and competitiveness (β = 0.31, p < 0.001). Additionally, core competencies positively impacted sustainability and competitiveness (β = 0.45, p < 0.001), confirming the mediating role of competencies in the HRD-performance linkage. The final structural model demonstrated good fit indices (CFI = 0.977, RMSEA = 0.075), affirming the model’s robustness. These findings underscore the importance of integrated HRD strategies tailored to rural tourism contexts, with implications for policy, training design, and sustainable development. The study highlights that well-structured HRD initiatives, including skill development, leadership training, and knowledge-sharing practices, can equip local communities with the capabilities required to adapt to market changes and environmental challenges. Strengthening competencies not only ensures long-term sustainability but also enhances the competitiveness of agro-tourism enterprises in domestic and international markets. Moreover, the results provide practical insights for policymakers and educators in designing interventions that align with community needs, thereby fostering inclusive growth and resilience in Thailand’s rural tourism sector.
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    Remotely sensed atmospheric anomalies of the 2022 Mw 7.0 Bantay, Philippines earthquake
    (2025-02-15)
    Khan, Sohrab
    ;
    Shah, Munawar
    ;
    Jamjareegulgarn, Punyawi
    ;
    El-Sherbeeny, Ahmed M.
    ;
    Abukhadra, Mostafa R.
    Remote sensing satellites have emerged as invaluable tools for surveilling natural disasters with more inevitable insights at various altitudes in atmosphere for various precursors. Moreover, the methods and satellite data before and after any event need more understanding for predicting the main shock due to the complexity of precursors. This study involves data from multiple sensors to assess how atmospheric parameters change in space and time over the Mw 7.0 Bantay, Philippines epicenter. The methods of statistical analysis, Nonlinear Autoregressive Network with Exogenous Inputs (NARX), and Multilayer Perceptron (MLP) are applied to various atmospheric parameters, including Land Surface Temperature (LST), Air Temperature (AT), Relative Humidity (RH), and Outgoing Longwave Radiation (OLR) to identify abnormal atmospheric patterns associated with earthquakes (EQ). These analyses focus on 3–5 days before the earthquake day. For this purpose, we trained daily average indices of atmospheric parameters for the month leading up to and the 15 days following the main shock. Since variations are irregular, detection can be challenging with classical statistics; therefore, we leveraged supervised machine learning to detect anomalies promptly and minimize the chances of missed detection. Thus, these findings support the lithosphere-atmosphere–ionosphere coupling (LAIC) hypothesis and suggest the need for further investigation in future research.