Over the past decades, network technologies across supply chains have been introduced and promoted with the premised benefits for all participants. However industry experience with an adoption process of some technology suggests that some firms have a great amount of uncertainty in estimating the benefits of its adoption. This uncertainty will lead to a slow adoption rates across population in supply chains. In my dissertation, I develop a model to analyze technology adoption in a two-level supply chain: multiple suppliers and multiple buyers. The uncertainty about the benefits is reduced as other firms adopt the technology and information from their experiences becomes available. Thus, at any given time, the estimate of benefit for a firm depends on the number of supplier firms and number of buyer firms who have already adopted the technology. I seek to capture this dependence and analyze its effect on the adoption of technology like radio frequency identification (RFID) technology both on analytical models and empirical study. This study also investigates several important aspects of technology adoption process in supply chains. The dissertation comprises three essays focusing on these aspects in a dynamic adoption process in a two-level supply chain and diffusion of technology in inter-firm networks. I investigate how the dynamic process of uncertainty resolution and environment factors affects the firm's adoption decisions, and empirically examines the diffusion of technology in supply chain networks with several hypotheses to test insights generated from the analytical model. [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://www.proquest.com/en-US/products/dissertations/individuals.shtml.]