A Comparison of Competing Models for Understanding Industrial Organization’s Acceptance of Cloud Services

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.

A Decision-Making Model for Adopting a Cloud Computing System

“…Low et al [29] identified technological, organizational, and environmental contexts with factors which were proposed in prior studies to understand decision components of cloud adoption. Chen et al [30] researched best-fitting models for adopting cloud services in an organization. Walther et al [31] developed a measurement index for accessing cloud system success with system quality, information quality, and net benefits.…”

Developing a Conceptual Model for the Intention to Adopt CC Saas

“…Thus, combining TOE variables strengthen the DOI theory has been accepted as a valuable idea [5]. The internal and external organisational characteristics of DOI have similar measurements like those of TOE's organisation context [7]. Despite the similarities, there are some key differences between the TOE and DOI.…”

Mining Braces of Innovation Linking to Digital Transformation Grounded in TOE Framework

“…A framework that would be beneficial in facilitating the understanding of digital transformation and innovation success is the technology-organization-environment (TOE), which classifies three areas that affect the process by which organizations implement or adopt technology. TOE has advanced to become a valuable theoretical lens for understanding new technology adoption for applicability in an organization [39] and a widespread theoretical perspective related to performance and innovation [40][41][42]. It is worth noting that the TOE framework does not identify specific factors, as these should be determined according to the research setting and research questions.…”

“…The TOE theoretical framework, on the other hand, is introduced into the research of enterprise digital innovation, which not only enriches the perspective of digital innovation research, but also broadens the application scope of the TOE model, that is to say, it breaks through the traditional application scenario analysis framework based on adopting innovative technologies. This is a response to existing research calling for practice in the areas of government policy, business model innovation, performance, and digital transformation [40][41][42], further exploring the specific connotation of the TOE framework in the Chinese context.…”