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dc.contributor.authorPramodha, MWS
dc.contributor.authorPradeep, RMM
dc.date.accessioned2024-03-26T05:59:14Z
dc.date.available2024-03-26T05:59:14Z
dc.date.issued2023-01
dc.identifier.urihttp://ir.kdu.ac.lk/handle/345/7537
dc.description.abstractThis study conducts a systematic review and evaluation of web-based project management systems to identify their features, strengths, and weaknesses in order to assess their suitability for Sri Lankan Online Micro-entrepreneurs. Therefore, this acts as a guide for Sri Lankan micro-entrepreneurs when choosing the most suitable project management system for their enterprises. Moreover, this study produces recommendations for future developments that can address the needs in the Sri Lankan micro-entrepreneurial arena. When considering academic literature focused on the use of project management tools and techniques in the performance of organizations, there exists a considerable research gap, because most of them are conducted regarding large firms, leaving a larger gap to explore this aspect in the context of Small and Mid-Sized enterprises. So, this study intends to address that gap. By reviewing the existing academic literature and conducting surveys using Sri Lankan online micro-entrepreneurs, this study assesses the suitability of five selected web-based project management systems for the Sri Lankan online micro-entrepreneurial context. As this study implies, Sri Lankan online microentrepreneurs face some challenges when adopting project management systems to their operations. As various web-based project management systems possess diverse characteristics, it is possible to evaluate the systems and choose the best fitting webbased project management system for micro-entrepreneurial digital ventures, and this study provides a contribution to that evaluation process.en_US
dc.language.isoenen_US
dc.subjectPredictive analytics,en_US
dc.subjectPoint of sale,en_US
dc.subjectHospitality industry,en_US
dc.subjectFood wasteen_US
dc.titleEfficient Hotel Stock Optimization and Food Waste Reduction System for Enhanced Customer Service and Menu Management Applying Predictive Analyticsen_US
dc.typeArticle Abstracten_US
dc.identifier.facultyFaculty of Computingen_US
dc.identifier.journalKDU SSFOCen_US


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