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Exploring Big Data Capability: Drivers and Impact on Supply Chain Performance

Lin, Canchu
http://rave.ohiolink.edu/etdc/view?acc_num=toledo1460732261

Abstract Details

2016, Doctor of Philosophy, University of Toledo, Manufacturing and Technology Management.
Although success stories of some big companies have been reported in the popular press, Big Data remains underexplored in supply chain management research. This project takes the initiative in investigating the role of Big Data in supply chain performance. Specifically, this project develops the construct of Big Data capability to characterize what is involved in Big Data and how companies use it to develop their competitive advantage. Then, the project moves to identify some key antecedents of the development of Big Data capability. Next, the project explores how Big Data capability facilitates the knowledge management process in the supply chain. Finally, the project seeks to measure the impact of knowledge management enacted by Big Data capability on performance. The project used the survey methodology to collect data to empirically assess the validity of the above outlined theoretical model. Data analysis results indicate that: 1) technology orientation facilitates the development of Big Data capability; 2) developmental culture negatively moderates the relationship between technology orientation and the development of Big Data capability; 3) Big Data capability positively impacts firms performance in new product development and product improvement by enhancing their knowledge management process; and 4) relationship building positively moderates that process.
Anand Kunnathur (Committee Chair)
Jerzy Kamburowski (Committee Member)
Michael Mallin (Committee Member)
David Black (Committee Member)
180 p.
Management
Big Data Capability, strategic orientations, developmental culture, knowledge co-creation, knowledge sharing, new product development, product improvement

Recommended Citations

Citations

  • Lin, C. (2016). Exploring Big Data Capability: Drivers and Impact on Supply Chain Performance [Doctoral dissertation, University of Toledo]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1460732261

    APA Style (7th edition)

  • Lin, Canchu. Exploring Big Data Capability: Drivers and Impact on Supply Chain Performance. 2016. University of Toledo, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=toledo1460732261.

    MLA Style (8th edition)

  • Lin, Canchu. "Exploring Big Data Capability: Drivers and Impact on Supply Chain Performance." Doctoral dissertation, University of Toledo, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1460732261

    Chicago Manual of Style (17th edition)

toledo1460732261
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© 2016, all rights reserved.
This open access ETD is published by University of Toledo and OhioLINK.