Purpose – The purpose of this paper is to integrate TAM model and TOE framework for cloud computing adoption at organizational level. Design/methodology/approach – A conceptual framework was developed using technological and organizational variables of TOE framework as external variables of TAM model while environmental variables were proposed to have direct impact on cloud computing adoption. A questionnaire was used to collect the data from 280 companies in IT, manufacturing and finance sectors in India. The data were analyzed using exploratory and confirmatory factor analyses. Further, structural equation modeling was used to test the proposed model. Findings – The study identified relative advantage, compatibility, complexity, organizational readiness, top management commitment, and training and education as important variables for affecting cloud computing adoption using perceived ease of use (PEOU) and perceived usefulness (PU) as mediating variables. Also, competitive pressure and trading partner support were found directly affecting cloud computing adoption intentions. The model explained 62 percent of cloud computing adoption. Practical implications – The model can be used as a guideline to ensure a positive outcome of the cloud computing adoption in organizations. It also provides relevant recommendations to achieve conducive implementation environment for cloud computing adoption. Originality/value – This study integrates two of the information technology adoption models to improve predictive power of resulting model.

Purpose-The purpose of this paper is to review the literature on information technology adoption in organizations to understand the need of integrated models for technology adoption. It further makes an attempt to identify key parameters to integrate technology acceptance model (TAM) and technology-organization-environment (TOE) framework for firm level technology adoption. This integration is intended to improve predictive power of resulting model. Design/methodology/approach-The research papers are accessed from the popular databases from 2000 to 2012. The selected papers have addressed technology adoption in context of recent technologies such as e-commerce, ERP, RFID, EDI and knowledge management, etc. The paper attempts to review the studies based on TAM model and TOE framework to identify relevant set of variables for the adoption of these technologies in organizations. Findings-TAM and its extended versions have high capability to explain the technology adoption while the significance of TOE framework is similarly recognized in explaining technology adoption. This review presents a holistic picture of a set of variables which can be used in the adoption of similar technologies in future. Further, the study has advocated the integration of TAM model and TOE framework to improve their explanatory power in technology adoption. The identified set of variables of TAM model and TOE framework can be used to integrate the two. Guidelines for integrating the two are also explained. Research limitations/implications-This study provides a platform for studying adoption of similar technologies using integration of TAM and TOE. Practical implications-The researchers and managers can use the set of variables identified for adoption of similar technologies in organizations. Originality/value-The review presents a set of variables which can be used to study adoption of similar technologies in future.

This article aims to propose an extended technology acceptance model-technical-organizationenvironment (TAM-TOE) framework and to develop its measures for cloud-computing adoption in organizations. Information technology adoption literature based on the TAM model and the TOE framework was reviewed to identify a set of variables relevant to cloud computing adoption. A conceptual framework was developed to integrate the TAM model and the TOE framework. Further, cloud-specific variables (security and third-party control) were also incorporated in the framework. This extended TAM-TOE framework was qualitatively analyzed using an interview method which resulted in 12 of the variables relevant to cloud-computing adoption. Further, a questionnaire was designed, pre-tested and surveyed to develop reliable measures of cloud-computing adoption. It resulted in conceptualizing an extended TAM-TOE framework for cloud-computing adoption and in developing its reliable measures. This study has a smaller sample size and is limited to cloud-computing adoption. On the other hand, it contributes towards the cloud-computing adoption literature. Managers can use measures identified to analyze their suitability for implementing cloud computing in their organizations. This article has a strong contribution in integrating the TAM model and the TOE framework, and developing measures for cloud-computing adoption.

Using extended Technology Acceptance Model (TAM), this study attempts to assess empirically crucial factors affecting cloud computing adoption intentions. It explores security, availability and compliance-related challenges in cloud computing and makes the necessary recommendation which can help to mitigate the risk in cloud computing. A framework was developed to test the effect of security, availability of cloud service provider and compliance-related factors on cloud computing adoption intentions mediated by perceived ease of use (PEOU) and perceived usefulness (PU). A questionnaire for the factors was developed to collect the data from 280 companies in information technology, manufacturing and finance sectors in India. The data was analyzed using exploratory and confirmatory factor analyses. Further, structural equation modelling using AMOS 20.0 was used to test the proposed model. The empirical results show that cloud computing adoption intention is determined by PU and PEOU. Further, PU is found to be significantly influenced by PEOU. Risk as well as availability and support are found to be significant on PEOU. In addition, threat, risk, vulnerability and compliance are found to be significant on PU. The model can be used as a guideline to ensure a positive outcome of the cloud computing adoption in organizations. The findings offer cloud computing users with a better understanding of how security, availability of cloud service provider and compliance-related factors affect cloud computing adoption intentions. It also provides relevant recommendations to achieve conducive implementation environment for cloud computing adoption. This study is an attempt to explore and develop model for cloud computing adoption intentions that was theoretically grounded in the TAM.

This article sought to identify the drivers of Big Data adoption within the manufacturing and services sectors in India. A questionnaire-based survey was used to collect data from manufacturing and service sector organizations in India. The data was analyzed using exploratory and confirmatory factor analyses. Relevant hypotheses were then derived and tested by SEM analysis. The findings revealed that the following factors are important for both sectors: relative advantage, compatibility, complexity, organizational size, top management support, competitive pressure, vendor support, data management and data privacy. Statistically significant differences between the service and the manufacturing sectors were found. In other words, the relative importance of the factors for Big Data adoption differs between the sectors. The only exception was complexity, which was found to be insignificant in regard to the manufacturing sector. The factors identified can be used to facilitate Big Data adoption outcomes in organizations.