Cloud computing is the next generation in computing, and the next natural step in the evolution of on-demand information technology services and products. However, only a few studies have addressed the adoption of cloud computing from an organizational perspective, which have not proven whether the research model is the best-fitting model. The purpose of this paper is to construct research competing models (RCMs) and determine the best-fitting model for understanding industrial organization's acceptance of cloud services. This research integrated the technology acceptance model and the principle of model parsimony to develop four cloud service adoption RCMs with enterprise usage intention being used as a proxy for actual behavior, and then compared the RCMs using structural equation modeling (SEM). Data derived from a questionnaire-based survey of 227 firms in Taiwan were tested against the relationships through SEM. Based on the empirical study, the results indicated that, although all four RCMs had a high goodness of fit, in both nested and non-nested structure comparisons, research competing model A (Model A) demonstrated superior performance and was the best-fitting model. This study introduced a model development strategy that can most accurately explain and predict the behavioral intention of organizations to adopt cloud services.

No abstract

The SONET network was designed to reduce the complexity, cost and number of transmission systems in the public network. To gain the full economic and, service benefits which. SONET may offer, new network planning tools must be developed. Domain knowledge representation and cost calculating algorithm are keystones for successful SONET planning. This paper presents a flexible SONET equipment cost modeling. The key concepts are generic equipment tree and parameter controlled top-down search. All available SONET equipments can be represented in a tree structure. Feasible equipment configuration can be generated by the top-down search and control parameter to calculate the installed first cost of the required network elements in various applications.