July'23
Welcome to the IUP Journal of Knowledge Management
Indigenous Knowledge Practices by Farmers in Response to Salinity Intrusion in Coastal Bangladesh
One of the main causes of soil degradation is salinization which adversely affects crop productivity and threatens the livelihood of resource-constrained small-scale farmers in coastal regions that are sensitive to climate change. Building adaptation plans requires an understanding of farmers' perspectives and indigenous adaptation techniques. This study focuses on soil salinity and its effects on small-scale farmers and their responses to it. The data were analyzed using descriptive statistics, including average and percentage, linear regression, and chi-square test. The findings demonstrated that the studied sites' soil salinity increased with time. The majority of farmers in the study areas believed that salinity had a detrimental effect on crop productivity, availability of freshwater for irrigation, cost of irrigation water, crop area, plant height, and crop size. The methods of indigenous knowledge adaptation varied depending on the locale. Surprisingly, the majority of farmers in extremely salinity-prone regions fell into the low adaptation category, whereas those in somewhat salinity-prone regions fell into the medium adaptation category. The unsuccessful adaptation to rising soil salinity may be a result of their lower educational level, small farm size, reliance on surface water, and lack of access to information and training. Therefore, all parties associated with those influencing elements should collaborate in a comprehensive effort to develop farmers' need-based, site-specific methods to solve the problem of salinity intrusion in the coastal sediments.
Knowledge Management for Human Resources: A Bibliometric Analysis
The relevance of knowledge management is growing day by day. Every firm concentrates on creating knowledge management strategies to survive in this dynamic environment, brought on by increased competition and globalization. Knowledge management is the key to success in business operations, particularly in the service sector, where buyers depend on knowledge of human resources. Hence, it is essential to look at the contributions in this field. The primary objective of this study is to do a bibliometric analysis of the role of knowledge management in human resource management, with a view to gaining a broad understanding of the previous research, current state, and trends in specific areas of business management.
Case Study
Artificial Intelligence Failure at IBM 'Watson for Oncology'
The case discusses the failure of International Business Machines' (IBM) artificial intelligence (AI) software Watson for Oncology (Watson). In 2012, the American multinational technology company partnered with New York-based cancer treatment center and research organization Memorial Sloan Kettering Cancer Center (MSK) to develop Watson that could provide medical professionals with improved access to up-to-date and comprehensive cancer data and practices. Despite Watson's Natural Language Processing (NLP) ability that enabled it to read and gain insights from unstructured data it was not able to interpret data as human doctors could. A 2017 investigation carried out by news website STAT revealed how IBM's AI software could not live up to the hype created around it by the company. To add to IBM's troubles, a 2017 audit carried out by the University of Texas showed that MD Anderson was using old data to train its OEA. The same year, i.e. in 2017, the cancer center closed down its project with IBM after spending $62 mn. With data quality and domain expertise being some of the major reasons for the failure of AI projects, is it worth it for companies such as IBM to invest in AI and Machine Learning (ML) tools in healthcare like Watson for Oncology without proper data preparation? This study looks at the roadblocks standing in the way of IBM finding success in using AI and ML in a bid to drive clinical research and drug discovery. It also examines how technology companies can make AI and ML a truly transformative force in healthcare.
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