Abstract
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.
Highlights
IntroductionBecause of its notable market-oriented and flexible architecture features, on-demand computing power, quick implementation, low maintenance, limited requirement for IT staff, and consequential lower costs, cloud computing has recently dominated IT press topics [2] and received increasing attention in both computer science and information systems (ISs) industries [3]
The official definition of cloud computing by the National Institute of Standards and Technology is as follows: “Cloud computing is a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources that can be rapidly provisioned and released with minimal management effort or service-provider interaction” [1]
This study developed four research competing models (RCMs) based on diffusion of innovations (DOI) theory, the TOE framework, and the principle of model parsimony, and compared the RCMs in two stages through structural equation modeling (SEM) for examining reasonable model fit, chi-square test, path coefficient significance, and squared multiple correlation (SMC, namely, model’s explanatory power) to identify the best-fitting model
Summary
Because of its notable market-oriented and flexible architecture features, on-demand computing power, quick implementation, low maintenance, limited requirement for IT staff, and consequential lower costs, cloud computing has recently dominated IT press topics [2] and received increasing attention in both computer science and information systems (ISs) industries [3]. Reviews of global primary market research conducted by firms have indicated substantial growth in the cloud service market for the foreseeable future. Global Cloud IT market revenue is predicted to increase from $180 billion in 2015 to $390 billion in 2020, attaining a CAGR of 17% [4]. Market Research Media [5] estimated that the global government cloud computing market is expected to grow at 6.7%
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