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. Hasan, R. Ashfaq, M. Parveen, T. and Gunardi, A. (2022) ‘Financial inclusion – does digital financial literacy matter for women entrepreneurs?’, International Journal of Social Economics, 50 (8), 1085
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are seeking highly motivated and innovative candidates with a background in business, economics, data science, or related fields. Prospective candidates should possess a strong interest in data-driven business
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of the following relevant subject areas: Information Science / Tech Management; Entrepreneurship / Innovation / Strategy Experience in qualitative and quantitative research methodologies is highly desirable. Fees
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business theory, and a keen interest in emerging business trends. Background in either of the following relevant subject areas: Information Science / Tech Management; Entrepreneurship / Innovation / Strategy
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analytical prowess, a strong foundation in economic and business theory, and a keen interest in emerging business trends. Background in either of the following relevant subject areas: Information Science
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Overview Multinational Corporations have a great opportunity to advance Sustainable Development Goals (SDGs). This is more so in developing regions such as Africa that face huge challenges meeting SDGs. Despite the significance placed on MNCs and in particular, the mining industry as one of the...
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Overview The travel and hospitality industry has experienced growth post Covid19, fostering collaboration among platforms and other industry players (Bahar, Nenonen, & Starr Jr, 2022; Vinogradov, Leick, & Kivedal, 2020). To attract and retain customers, hotels increasingly collaborate with...
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in psychology or relevant social science, and relevant research experience. Fees and funding The PhD is fully funded, including a bursary (~£18,622/year), and tuition fees, for its 3 year duration.
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with ethnobotanical assessments and socioeconomic evaluations, The goal is to devise and develop participatory, science-based and socially accountable restoration methods for socio-ecologically
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energy systems, this project will us use artificial intelligence and data sciences methods (like technology feasibility modelling), to simulate and assess the energy needs of local homes. The research will