Field Test Report
Field Test Report – Qualitative Study Interviews Hardik Patel Business PhD. 03/25/2024 IRB Committee, University of the Cumberland’s Dear IRB Committee Members, I am pleased to present the field test report of our qualitative study interviews for your review and consideration. This report outlines the findings and insights gathered during the field test, which aimed to assess the feasibility and effectiveness of our interview methodology. Introduction The objective of conducting the field test was to assess the efficacy of our interview approach in How corporate social responsibility affects the financial performance of small businesses in western Kentucky. This report aims to present the results and observations gleaned from interviews conducted with two participants: Participant A, an owner of Hickory & oak Restaurant, and Participant B, an owner of Giorgio’s Menswear and Tuxedo. Field Test Participants Interviews were carried out with two participants: Participant A, an owner of Hickory & oak Restaurant, and Participant B, an owner of Giorgio’s Menswear and Tuxedo. Both participants brought extensive expertise in corporate social responsibility to small businesses in western Kentucky. Interview Process The interviews took place personally with Participant A and Participant B to accommodate their schedules. A semi-structured interview approach was employed for both sessions, comprising openended questions designed to delve into different aspects of AI and ML in project management. The interview guides addressed topics such as the application of predictive analytics technology, challenges experienced during implementation, perceived effects on project management efficiency, and suggestions for enhancement. Summary Participant A and Participant B provided insightful perspectives on the integration of AI and ML technologies into project management practices within their respective organizations. They discussed challenges faced during implementation, including issues with data integration and the need for specialized expertise. Additionally, they highlighted the importance of predictive analytics technology in enhancing project management efficiency. Despite these hurdles, both speakers emphasized the overall advantages of AI and ML for project management effectiveness, citing improvements in resource allocation and workflow efficiency. With a focus on long-term benefits for their companies, they expressed support for further integrating AI and ML technology into project management operations. Recommendations Based on the insights gathered from the interviews with participant A and B, several recommendations are proposed for refining the interview questions for the main study: This study aims to dive deeper into the distinct issues faced in data integration while implementing artificial intelligence (AI) and machine learning (ML) technologies in various corporate scenarios. Examine in greater detail the particular difficulties faced when incorporating AI and ML technologies, such as opposition from the company, cultural obstacles, and concerns around the security of data. Acquiring in-depth knowledge of these difficulties will yield a thorough comprehension of the aspects that impact the effective implementation of AI and ML in project management. Incorporate questions aimed at evaluating the performance metrics and key performance indicators (KPIs) used for quantifying the influence of artificial intelligence (AI) and machine learning (ML) technologies on the efficiency and success of project management. The comprehension of how firms measure the advantages of adopting artificial intelligence (AI) and machine learning (ML) can aid in the selection of significant indicators for assessing success. Thank you for your time and consideration. We look forward to discussing the findings of our field test and addressing any questions or concerns you may have. Sincerely, Hardik Patel Project manager [email protected] (364) 203 9051
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