An experimental investigation of the impact of using big data analytics on customers’ performance measurement

dc.AffiliationOctober University for modern sciences and Arts (MSA)
dc.contributor.authorElkmash, Marwa Rabe Mohamed
dc.contributor.authorAbdel-Kader, Magdy Gamal
dc.contributor.authorEl Din, Bassant Badr
dc.date.accessioned2021-02-06T11:52:58Z
dc.date.available2021-02-06T11:52:58Z
dc.date.issued2021
dc.descriptionScopusen_US
dc.description.abstractPurpose: This study aims to investigate and explore the impact of big data analytics (BDA) as a mechanism that could develop the ability to measure customers’ performance. To accomplish the research aim, the theoretical discussion was developed through the combination of the diffusion of innovation theory with the technology acceptance model (TAM) that is less developed for the research field of this study. Design/methodology/approach: Empirical data was obtained using Web-based quasi-experiments with 104 Egyptian accounting professionals. Further, the Wilcoxon signed-rank test and the chi-square goodness-of-fit test were used to analyze data. Findings: The empirical results indicate that measuring customers’ performance based on BDA increase the organizations’ ability to analyze the customers’ unstructured data, decrease the cost of customers’ unstructured data analysis, increase the ability to handle the customers’ problems quickly, minimize the time spent to analyze the customers’ data and obtaining the customers’ performance reports and control managers’ bias when they measure customer satisfaction. The study findings supported the accounting professionals’ acceptance of BDA through the TAM elements: the intention to use (R), perceived usefulness (U) and the perceived ease of use (E). Research limitations/implications: This study has several limitations that could be addressed in future research. First, this study focuses on customers’ performance measurement (CPM) only and ignores other performance measurements such as employees’ performance measurement and financial performance measurement. Future research can examine these areas. Second, this study conducts a Web-based experiment with Master of Business Administration students as a study’s participants, researchers could conduct a laboratory experiment and report if there are differences. Third, owing to the novelty of the topic, there was a lack of theoretical evidence in developing the study’s hypotheses. Practical implications: This study succeeds to provide the much-needed empirical evidence for BDA positive impact in improving CPM efficiency through the proposed framework (i.e. CPM and BDA framework). Furthermore, this study contributes to the improvement of the performance measurement process, thus, the decision-making process with meaningful and proper insights through the capability of collecting and analyzing the customers’ unstructured data. On a practical level, the company could eventually use this study’s results and the new insights to make better decisions and develop its policies. Originality/value: This study holds significance as it provides the much-needed empirical evidence for BDA positive impact in improving CPM efficiency. The study findings will contribute to the enhancement of the performance measurement process through the ability of gathering and analyzing the customers’ unstructured data. © 2021, Emerald Publishing Limited.en_US
dc.identifier.otherDOI 10.1108/ARJ-04-2020-0080
dc.identifier.urihttp://repository.msa.edu.eg/xmlui/handle/123456789/4417
dc.identifier.urihttps://www.scimagojr.com/journalsearch.php?q=19600162139&tip=sid&clean=0
dc.language.isoen_USen_US
dc.publisherEmerald Publishing Limiteden_US
dc.relation.ispartofseriesAccounting Research Journal;1030-9616
dc.subjectOctober University for Technology acceptance modelen_US
dc.subjectBig data analyticsen_US
dc.subjectDiffusion of innovation theoryen_US
dc.subjectCustomer performance measurementen_US
dc.titleAn experimental investigation of the impact of using big data analytics on customers’ performance measurementen_US
dc.typeArticleen_US

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