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Purpose:The authors examine the literature on Enterprise Resource Planning (ERP) to establish whether the Critical Success Factors (CSFs) for achieving stages of an ERP project have been empirically shown to be 'critical'. Methodology:The authors used a systematic approach to review 627 refereed papers published between 1998 and 2010 on ERP, from which 236 papers related to CSFs on ERP were selected for analysis. The authors employed procedures from qualitative and interpretive research methods, to analyse and interpret the material using five-step procedure of gathering, categorising, coding, analysing and comparing the data. Findings: Prior studies have identified a large number of CSFs for ERP implementation success or improved performance outcomes. The authors have shown that a limited number of CSFs have been empirically investigated for their role in, and effect on, implementation success or post-implementation performance outcomes. While reporting the factors that have some evidence to support them, the authors question the utility of the general concept of CSFs. Research implications: The authors' findings question the validity of many of the claimed CSFs and the utility of the general body of literature on CSFs. The authors caution researchers who may plan to use claimed CSFs for ERP in their research to carefully examine the veracity of the claim before proceeding. Practical implications: The findings can help managers to focus their attention, priorities, resources and leadership on managing the CSFs that have been established to be critical for achieving ERP project implementation and/or performance outcomes. Originality/value: The results provide new insights into the usefulness of CSFs and indicate that merely identifying possible CSFs is not sufficient to help with ERP success. Further 'This article is

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Social media has brought about a revolution and dictated a paradigm shift in the operational strategies of firms globally. It has resulted in collection of massive data from a variety of social media channels, necessitating use of this data for business intelligence purposes. Despite its importance, little research exists on the implications of the use of Big Data analytics for business intelligence purposes. This study fills this gap in knowledge by examining the role and implication of Big Data analytics on business intelligence for the data collected from Social media channels in China. Given the exploratory nature of the research, the study takes a qualitative approach to data collection and analysis. Based on an extensive literature review, the study has developed a robust semi-structure questionnaire. We plan to conduct approximately 35-40 interviews with respondents such as IT managers, IT consultants, and Senior Business managers among others from a wide range of industries including retail and manufacturing settings. The data will be analysed using Nvivo to identify issues that are critical for creating value through Big Data analytics for business intelligence purposes. The results have significant impact for both theory and practice to devise plans and strategies to optimise the benefits of social-media channels for business value.