Cloud Computing: TOE Adoption Factors By Service Model In Manufacturing

Abstract

Organizations are adopting cloud technologies for two primary reasons: to reduce costs and to enhance business agility. The pressure to innovate, reduce costs and respond quickly to changes in market demand brought about by intense global competition has U.S. manufacturing firms turning to cloud computing as an enabling strategy. Cloud computing is a service based information technology model that enables on-demand access to a shared pool of computing services provisioned over a broadband network. Cloud is categorized across three primary service models, Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS), differentiated by the cloud provider’s level of responsibility for managing hardware services, development platforms and application services. While prior research in cloud computing has sought to define the concept and explore the business value, empirical studies in the Information Systems literature stream are sparse, limited to exploratory case studies and SaaS research. Using the Technology, Organization, and Environment framework as a theoretical foundation, this research provides a holistic cloud adoption model inclusive of all cloud service layers. The study analyzes factors influencing organizational cloud adoption utilizing survey data from 150 U.S. manufacturing firms. The results find organizational innovativeness as a crucial factor to cloud computing adoption in manufacturing. An inverse factor relationship suggests the more innovative the firm culture, the less likely it is to adopt cloud. Other significant adoption factors include trust and technical competency. Findings also suggest variations in adoption influences based on the cloud service model deployed. The study has strategic implications for both researchers and managers seeking to understand the antecedents to adoption, and for practitioners developing an organizational cloud strategy spanning multiple cloud service models. For vendors, the study provides insights that can be leveraged to inform product design, solution strategy, and value proposition creation for future cloud service offerings.

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