Disentangling the Relationship Between the Adoption of In-Memory Computing and Firm Performance

Marua Fay, Oliver Müller, Jan vom Brocke

Research output: Journal Article or Conference Article in JournalConference articleResearchpeer-review

Abstract

Recent growth in data volume, variety, and velocity led to an increased demand for high-performance data processing and analytics solutions. In-memory computing (IMC) enables organizations to boost their information processing capacity, and is widely acknowledged to be one of the leading strategic technologies in the field of enterprise systems. The majority of technology vendors now have IMC technologies in their portfolio, and the interest of companies in adopting such solutions in order to benefit from big data is increasing. Although there is first research on the business value of IMC in the form of case studies, there is a lack of large-scale quantitative evidence on the positive effect of such solutions on firm performance. Based on a unique panel data set of IMC adoption information and financial firm performance data for a sample of companies from the Fortune 500 list this study aims at explaining the relationship between the adoption of IMC solutions and firm performance. In this research-in-progress paper we discuss the theoretical background of our work, describe the proposed research design, and develop five hypotheses for later testing. Our work aims at contributing to the
research streams on IT business value and business analytics by helping to better understand the nature of the interdependencies between IMC adoption and firm performance.
Original languageEnglish
JournalProceedings / European Conference on Information Systems (ECIS)
Pages (from-to)1-11
ISSN0000-0034
Publication statusPublished - 2016

Keywords

  • Data Processing
  • In-Memory Computing
  • Enterprise Systems
  • Big Data Analytics
  • Firm Performance

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