Big Data Technology and Technological Capability
Presentation and Thesis Link:
Big Data has received great attention in academic literature and industry papers. This presentation is based on research findings of doctoral research on big data technology acceptance. This research has made an attempt to identify factors that influence big data technology acceptance. With help of extant literature, industry technical white papers, vendor publications on data management technologies ranging from conventional data warehousing to big data storage technologies (e.g., Hadoop Distributed File System) about three dozen factors have been identified. Through a qualitative study using industry big data experts twelve factors have been shortlisted for further study. A survey was conducted in which 349 respondents participated. The statistical analyses of survey data reveal that out of 12 independent variables eight independent variables are significant. This study successfully tests and validates four new variables relating to technological capabilities in adopting new technology: scalability, data storage, and processing capability, flexibility, and reliability. These findings advance theory and contribute to the foundation for future research aimed at improving our understanding of Hadoop user adoption behavior. From the practitioners' point of view, this research provides companies with insights as to what technological features and capabilities to look for when buying a complex technology.
Nayem Rahman is an Information Technology (IT) professional. He has implemented several large projects using data warehousing and big data technologies in enterprise DSS platforms. He holds a Ph.D. degree in Technology Management (big data tech adoption) from Portland State University, an M.S. in Systems Science (Modeling & Simulation) from Portland State University, Oregon, and an MBA in Management Information Systems (MIS), Project Management, and Marketing from Wright State University, Ohio, USA. He has presented his research in both industry (Teradata Partners, 2005 & 2008; Intel’s Supply Chain Tech Leadership Forum, 2015) and academic (AMCIS, 2008; IEEE Canada, 2013; ASEM, 2018) conferences. He has authored more than 40 articles published in various conference proceedings and scholarly journals. He serves on the Editorial Review Board of the International Journal of End-User Computing and Development (IJEUCD) and International Journal of Technology Diffusion (IJTD). His principal research areas are Changed Data Capture and Management in Temporal Data Warehouses, HANA In-Memory Databases, Performance Optimization in Database Systems, Big Data Analytics, Technology Adoption, and Sustainability of Information Technology. Nayem is based in Oregon, USA.