An Integrative Model of Clients\u27 Decision to Adopt an Application Service Provider

Application Services Providers (ASPs) exploit the economics of delivering commercial off-the-shelf software over the Internet to many dispersed users, but the decision-making process to adopt the ASP business model can be complex requiring a comprehensive consideration of various factors. As a new form of outsourcing, the ASP business model differs from traditional outsourcing models with respect to the attributes associated with vendors, clients, and applications. These differences are expected to demand decision models that are distinct from those in the traditional IS outsourcing. In this study, an integrative model for ASP adoption that incorporates economic determinants, strategic determinants, and social determinants is developed. This integrative model includes the individual effects of these determinants, as well as the moderating effects of the social determinants upon the economic and strategic determinants. To test this research model and its associated hypotheses, two self-administered surveys, one among clients of a leading ASP and the other among nationally selected top computer executives, are conducted. The findings from the two surveys show that economic, strategic and social factors impact a client’s decision on ASP adoption. Moreover, among prospective ASP adopters, trust had a strong tendency to influence the effect of cost benefits and IT deficiency removal on ASP adoptions. This study empirically examines the determinants of ASP adoption from an integrative perspective. This model contributes to the academic literature by presenting a broad view for understanding ASP adoption decision. The findings from the survey elucidate the independent impact of the economic, social and strategic perspectives as well as interactions among the three perspectives for ASP adoption. For practitioners, this study can shed insight on special determinants in ASP adoption. It can help ASPs gain a better understanding of clients’ concerns for ASP adoption and make corresponding adjustments in the services in order to attract clients and increase application usage

Global synchronization for discrete-time stochastic complex networks with randomly occurred nonlinearities and mixed time delays

Copyright [2010] IEEE. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Brunel University's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to [email protected]. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.In this paper, the problem of stochastic synchronization analysis is investigated for a new array of coupled discrete-time stochastic complex networks with randomly occurred nonlinearities (RONs) and time delays. The discrete-time complex networks under consideration are subject to: (1) stochastic nonlinearities that occur according to the Bernoulli distributed white noise sequences; (2) stochastic disturbances that enter the coupling term, the delayed coupling term as well as the overall network; and (3) time delays that include both the discrete and distributed ones. Note that the newly introduced RONs and the multiple stochastic disturbances can better reflect the dynamical behaviors of coupled complex networks whose information transmission process is affected by a noisy environment (e.g., Internet-based control systems). By constructing a novel Lyapunov-like matrix functional, the idea of delay fractioning is applied to deal with the addressed synchronization analysis problem. By employing a combination of the linear matrix inequality (LMI) techniques, the free-weighting matrix method and stochastic analysis theories, several delay-dependent sufficient conditions are obtained which ensure the asymptotic synchronization in the mean square sense for the discrete-time stochastic complex networks with time delays. The criteria derived are characterized in terms of LMIs whose solution can be solved by utilizing the standard numerical software. A simulation example is presented to show the effectiveness and applicability of the proposed results

Network Sketching: Exploiting Binary Structure in Deep CNNs

Convolutional neural networks (CNNs) with deep architectures have substantially advanced the state-of-the-art in computer vision tasks. However, deep networks are typically resource-intensive and thus difficult to be deployed on mobile devices. Recently, CNNs with binary weights have shown compelling efficiency to the community, whereas the accuracy of such models is usually unsatisfactory in practice. In this paper, we introduce network sketching as a novel technique of pursuing binary-weight CNNs, targeting at more faithful inference and better trade-off for practical applications. Our basic idea is to exploit binary structure directly in pre-trained filter banks and produce binary-weight models via tensor expansion. The whole process can be treated as a coarse-to-fine model approximation, akin to the pencil drawing steps of outlining and shading. To further speedup the generated models, namely the sketches, we also propose an associative implementation of binary tensor convolutions. Experimental results demonstrate that a proper sketch of AlexNet (or ResNet) outperforms the existing binary-weight models by large margins on the ImageNet large scale classification task, while the committed memory for network parameters only exceeds a little.Comment: To appear in CVPR201

Electronic Voting System Characteristics and Voter Participation Intention

The rapid development of communication and information technology has made electronic voting techno- logically and economically feasible. In this study, we will examine the differential impact of four electronic voting system (EVS) characteristics (privacy, accessibility, mobility, and accuracy) on voter participation intention (i.e., EVS voting) and on preferred EVS mechanism (telephone, Web-based, or touch-screen) for electronic voting

Technology-Organization-Environment Meta-Review and Construct Analysis: Insights for Future Research

The Technology-Environment-Organization (“T-O-E”) framework has been widely applied in more than 80 published empirical information systems (“IS”) studies across multiple stages of organizational technology innovation adoption research in IS since its introduction in 1990. No prior review has traced studies and their factors back to the original framework categories and sub-categories to identify the existing lack of coverage. We address this research gap to guide future work. We present a meta-review and construct analysis derived from the most comprehensive collection of T-O-E articles collected and reviewed up to now. We present four major research contributions: 1) a guide to T-O-E constructs, 2) identification of new organizational sub-categories, 3) recognition of the existing levels of factor miscategorization, 4) identification of measurement gaps particularly relating to linking and communications sub-categories

Physics Inspired Optimization on Semantic Transfer Features: An Alternative Method for Room Layout Estimation

In this paper, we propose an alternative method to estimate room layouts of cluttered indoor scenes. This method enjoys the benefits of two novel techniques. The first one is semantic transfer (ST), which is: (1) a formulation to integrate the relationship between scene clutter and room layout into convolutional neural networks; (2) an architecture that can be end-to-end trained; (3) a practical strategy to initialize weights for very deep networks under unbalanced training data distribution. ST allows us to extract highly robust features under various circumstances, and in order to address the computation redundance hidden in these features we develop a principled and efficient inference scheme named physics inspired optimization (PIO). PIO's basic idea is to formulate some phenomena observed in ST features into mechanics concepts. Evaluations on public datasets LSUN and Hedau show that the proposed method is more accurate than state-of-the-art methods.Comment: To appear in CVPR 2017. Project Page: https://sites.google.com/view/st-pio