Examinando por Autor "Begum, Abida"

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    Contribution of Small-Scale Agroforestry to Local Economic Development and Livelihood Resilience: Evidence from Khyber Pakhtunkhwa Province (KPK), Pakistan
    (MDPI, 2022-01) Zada, Muhammad; Zada, Shagufta; Ali, Mudassar; Zhang, Yongjun; Begum, Abida; Han, Heesup; Ariza-Montes, Antonio; Araya-Castillo, Luis
    Agroforestry plays a vital role in enhancing environmental sustainability, improving local economies, and reducing poverty through livelihood resilience. Several researchers have studied the importance of agroforestry, but little attention has been paid to livelihood resilience and local economic development in developing countries. This study aims to find the role of small-scale agroforestry in local economic development in the Shangla and Swat districts of Khyber Pakhtunkhwa (KPK) Province, Pakistan. In this study, a total of 350 quantitative household surveys, 12 qualitative household case studies, and interviews of experts are used. The ordinary least squares (OLS), linear regression model, household income, wealth index, and five capitals of sustainable livelihood approach (SLA) were used to measure livelihood resilience. Results show several significant findings which may apply on a larger scale and in other cities of Pakistan or other countries. First, it directly shows the association between agroforestry, resilience-building, and local economic development. Second, financial capital can be improved through agroforestry, which can improve other capital assets. Third, small-scale agroforestry brings non-financial benefits such as environmental sustainability, improved living standards, reduced soil erosion, and provided shade. Fourth, irrigation plays a vital role in building livelihood resilience and promoting agroforestry. Lastly, on-farm diversity can be improved through agroforestry. This research discusses several practical implications along with recommendations for future research. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.
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    Exploring the impact of linguistic signals transmission on patients’ health consultation choice: web mining of online reviews
    (MDPI, 2021-09) Shah, Adnan Muhammad; Ali, Mudassar; Qayyum, Abdul; Begum, Abida; Han, Heesup; Ariza-Montes, Antonio; Araya-Castillo, Luis
    Background: Patients face difficulties identifying appropriate physicians owing to the sizeable quantity and uneven quality of information in physician rating websites. Therefore, an increasing dependence of consumers on online platforms as a source of information for decision-making has given rise to the need for further research into the quality of information in the form of online physician reviews (OPRs). Methods: Drawing on the signaling theory, this study develops a theoretical model to examine how linguistic signals (affective signals and informative signals) in physician rating websites affect consumers’ decision making. The hypotheses are tested using 5521 physicians’ six-month data drawn from two leading health rating platforms in the U.S (i.e., Healthgrades.com and Vitals.com) during the COVID-19 pandemic. A sentic computing-based sentiment analysis framework is used to implicitly analyze patients’ opinions regarding their treatment choice. Results: The results indicate that negative sentiment, review readability, review depth, review spelling, and information helpfulness play a significant role in inducing patients’ decision-making. The influence of negative sentiment, review depth on patients’ treatment choice was indirectly medi-ated by information helpfulness. Conclusions: This paper is a first step toward the understanding of the linguistic characteristics of information relating to the patient experience, particularly the emerg-ing field of online health behavior and signaling theory. It is also the first effort to our knowledge that employs sentic computing-based sentiment analysis in this context and provides implications for practice. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.