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A Meta-Analysis of Impact of ERP Implementation

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Advances in Data Science and Management

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 37))

Abstract

In the era of globalization, most of the corporate focus on automating their systems to excel and enhance the capacity of the organization. In this context, a number of research papers have been published to understand the automated system process. The automated system is further named as Enterprise Resource Planning. In this article, the author tries to explore the Enterprise Resource Planning system, pre-implementation, post-implementation challenges, opportunities, and impact of the various scenario through published articles in reputed journals. For this study, the author has identified 101 reputed articles published from 2014 to 2018. The study has been segregated into five broad regions like pre- and post-implementation of Enterprise Resource Planning systems, extension, trend, and perspective and education. It was found that most of the developing and underdeveloped countries are heading to manage their convoluted operation with the help of some type of Enterprise Resource Planning systems available in the market with a number of challenges.

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Authors and Affiliations

  1. Sri Sri University, Cuttack, India

    Rajendra Kumar Behera & Sunil Kumar Dhal

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  1. Rajendra Kumar Behera
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  2. Sunil Kumar Dhal
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Correspondence to Rajendra Kumar Behera .

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Editors and Affiliations

  1. Department of Computer Application, SMIT, Sikkim Manipal University, Sikkim, India

    Samarjeet Borah

  2. Department of Automatics and Applied Software at the Faculty of Engineering, Aurel Vlaicu University of Arad, Arad, Romania

    Valentina Emilia Balas

  3. Faculty of Technical Sciences, Jan Wyzykowski University, Polkowice, Poland

    Zdzislaw Polkowski

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Behera, R.K., Dhal, S.K. (2020). A Meta-Analysis of Impact of ERP Implementation. In: Borah, S., Emilia Balas, V., Polkowski, Z. (eds) Advances in Data Science and Management. Lecture Notes on Data Engineering and Communications Technologies, vol 37. Springer, Singapore. https://doi.org/10.1007/978-981-15-0978-0_12

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