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ERIC Number: ED636744
Record Type: Non-Journal
Publication Date: 2023
Pages: 240
Abstractor: As Provided
ISBN: 979-8-3798-9516-7
ISSN: N/A
EISSN: N/A
Impact of Big Data Implementation on Decision-Making and Organizational Outcomes in the Real Estate Construction Enterprises
Desiree Walton
ProQuest LLC, Ed.D. Dissertation, Pepperdine University
Decision-making, a key factor of organizational performance, is based on information retrieved from processing raw data. As businesses and consumers are shifting toward digital channels, more and more data is being generated through digital services and electronic devices. Big Data is argued to have significant benefits to businesses, and yet data analytics companies are growing much slower compared to the growth in the volume of generated Big Data. In particular, the adoption of Big Data solutions in construction companies is relatively low, despite potential benefits in terms of efficiency and sustainability. The present study aimed to critically assess the impact of Big Data use on decision-making and organizational outcomes in the context of the construction industry. A series of interviews were conducted with decision-makers of construction companies to explore their strategies in regard to the use Big Data, associated challenges, and the extent to which Big Data use was successful. The study adopted thematic analysis to process the codes from the interview transcripts. The findings suggest that interoperability and integration of Big Data into existing internal systems as well as the talent gaps in construction companies are the key challenges decision-makers had to face. The study recommends that construction companies hire IT experts, conduct regular workshops and training sessions, and adopt a top-down communication approach to overcome these challenges. The results can be valuable to practitioners and managers in construction firms. Finally, the study concludes by proposing a conceptual framework that construction companies can use to develop a better and more integrated framework for Big Data implementation. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://bibliotheek.ehb.be:2222/en-US/products/dissertations/individuals.shtml.]
ProQuest LLC. 789 East Eisenhower Parkway, P.O. Box 1346, Ann Arbor, MI 48106. Tel: 800-521-0600; Web site: http://bibliotheek.ehb.be:2222/en-US/products/dissertations/individuals.shtml
Publication Type: Dissertations/Theses - Doctoral Dissertations
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A