Evidence map›Paper›PMID 36844037›Full record

ArticleInformation systems frontiers : a journal of research and innovation2023

Enhancing ERP Responsiveness Through Big Data Technologies: An Empirical Investigation.

Florie Bandara, Uchitha Jayawickrama, Maduka Subasinghage, Femi Olan, Hawazen Alamoudi, Majed Alharthi

Abstract read
In one paragraph

Article in Information systems frontiers : a journal of research and innovation, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Florie BandaraSchool of Business and Economics, Loughborough University, Loughborough, LE11 3TU UK.
Uchitha JayawickramaSchool of Business and Economics, Loughborough University, Loughborough, LE11 3TU UK.ORCID 0000-0002-7159-6759
Maduka SubasinghageFaculty of Business, Economics and Law, Auckland University of Technology, 120 Mayoral Drive, Auckland, New Zealand.
Femi OlanEssex Business School, University of Essex, Southend-On-Sea, SS1 1LW UK.
Hawazen AlamoudiMarketing Department, College of Business, King Abdulaziz University, P.O. Box 344, Rabigh, 21911 Saudi Arabia.
Majed AlharthiFinance Department, College of Business, King Abdulaziz University, P.O. Box 344, Rabigh, 21911 Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Organizations are integrating big data technologies with Enterprise Resource Planning (ERP) systems with an aim to enhance ERP responsiveness (i.e., the ability of the ERP systems to react towards the large volumes of data). Yet, organizations are struggling to manage the integration between the ERP systems and big data technologies, leading to lack of ERP responsiveness. For example, it is difficult to manage large volumes of data collected through big data technologies and to identify and transform the collected data by filtering, aggregating and inferencing through the ERP systems. Building on this motivation, this research examined the factors leading to ERP responsiveness with a focus on big data technologies. The conceptual model which was developed through a systematic literature review was tested using Structural equation modelling (SEM) performed on the survey data collected from 110 industry experts. Our results suggested 12 factors (e.g., big data management and data contextualization) and their relationships which impact on ERP responsiveness. An understanding of the factors which impact on ERP responsiveness contributes to the literature on ERP and big data management as well as offers significant practical implications for ERP and big data management practice.

Indexed as

Big data technologiesERP responsivenessERP systemsStructural equation modellingSystematic literature review

Identifiers

PMID36844037
PMCPMC9938686

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.