Abstract

The emergence of cloud computing is quickly redefining the information technology (IT) and business landscape. Cloud computing involves delivery of IT infrastructure, software and platforms as a service to the end users. This IT acquisition model saves organizations from huge capital expenditures on IT and the burden of keeping a huge IT department to provide system support. Cloud computing as an IT innovation is steadily generating a lot of interest within IT innovation researchers and practitioners. Extant research in IT innovation has heavily relied on the dominant paradigm which explains and predicts innovation adoption on the basis of economic-rationalistic models. These models assume a direct relationship between an organization’s innovator profile and the quantity of adoption in terms of earliness, frequency and extent of adoption. Further, they have always assumed a positive relationship between the quantity of innovation and quality of innovation. The advent of radical IT innovations like cloud computing calls for a rethinking of the dominant paradigm in terms of its efficacy in explaining innovative behaviors in organizations. Organizations hoping to adopt cloud computing are in need of a unifying IT innovation model that will help them discern whether, when and how to innovate. That is, they are concerned about the quality of innovation. This study proposes an IT innovation adoption model that incorporates the concept of mindfulness as a moderating factor between quantity of innovation and quality of innovation. The proposed conceptual model is a result of a thorough literature review of the IT innovation adoption research. This study, though conceptual, enriches cloud computing research by proposing an IT innovation model that suits its radical nature compared to other IT innovations. The proposed model once validated will also be of valuable use to practitioners and researchers interested in cloud adoption.

Highlights

  • Information Technology has always played the role of a disruptive force that somehow connects discontinuities and changes business models, ecosystems or even the world order

  • The main challenge is that of reliability, arising from the fact that cloud computing platform is a complex network involving different players

  • The dominant paradigm, which has so far informed IS research in Information Technology (IT) innovation, may not be the best model to explain cloud adoption. This is because cloud computing is a radical IT innovation

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Summary

Introduction

Information Technology has always played the role of a disruptive force that somehow connects discontinuities and changes business models, ecosystems or even the world order. Studies using the dominant paradigm models have mainly focused on the relationship between the innovator profile of an organization and the quantity of innovation (timing, rate and implementation of IT innovation). These studies have been criticized for not being able to allow for complex interactions among the factors that go beyond simple linear or multiplicative effects (Fichman, 2004). The dominant paradigm models assume that there is always a positive relationship between the quantity of innovation and the quality of innovation, conceptualized as the performance outcomes (Fichman, 2004) Studies such as Ragin (1999) that used the innovation configuration perspective suggest that this may not be true. The conclusion follows to reiterate the purpose of the study and possible future IT innovation research frontiers

The Genesis of Cloud Computing
Cloud Computing Ontology
Cloud Service Models
Cloud Deployment Models
Cloud Challenges
Reliability in Cloud Computing
Literature Review
Theoretical Literature
The Dominant Paradigm and Its Theories
The Sociological Perspective
Reliability in IS Research
Challenging the Dominant Paradigm
Toward Innovation Mindfulness
The Theory of Mindfulness
Individual Mindfulness
Collective Mindfulness
Re-Conceptualizing IT Innovation Variables
The Independent Variables
The Moderating Variables
Preoccupation with Failure
Reluctance to Simplify Interpretations
Attention to Operations
Commitment to Resilience
Under Specification of Structure
The Dependent Variable
Conclusion
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