This study examines smartphone adoption behavior among American college students by combining all components of innovation diffusion theory (IDT), the technology acceptance model (TAM), the value‐based adoption model (VAM), and the social influence (SI) model. Data indicate that the smartphone adoption rates are beyond the early majority and are now approaching the late majority. The findings of analysis of variance tests revealed that all variables of TAM, VAM, and SI varied across the adopter groups: The current adopter's mean values of the variables were the highest, followed by those of potential and nonadoption groups. Multinomial logistic regression (MLR) analyses revealed that perceived value and affiliation mainly determine the different perceptions of adoption groups. Smartphone adoption, however, was relatively unaffected by perceived ease of use and perceived usefulness. Perceived popularity, perceived price, and ethnicity played a role in distinctive determinants between current adopters and nonadopters. The results imply that adopters perceive smartphones as not only a worthwhile device in which to invest money but also a symbolic device to signal their affiliation and timely technology adoption. Another intriguing finding is the differences of interest in contents between current adopters and nonadopters. Social interactions via social networking services, acquisition for lifestyle, information seeking, and entertainment via gaming were the main applications of interest.

We present decentralized algorithms that compute minimum-cost subgraphs for establishing multicast connections in networks that use coding. These algorithms, coupled with existing decentralized schemes for constructing network codes, constitute a fully decentralized approach for achieving minimum-cost multicast. Our approach is in sharp contrast to the prevailing approach based on approximation algorithms for the directed Steiner tree problem, which is suboptimal and generally assumes centralized computation with full network knowledge. We also give extensions beyond the basic problem of fixed-rate multicast in networks with directed point-to-point links, and consider the case of elastic rate demand as well as the problem of minimum-energy multicast in wireless networks.